bigquery

package module
v1.39.0 Latest Latest
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 Go to latest Published: Aug 23, 2022 License: Apache-2.0 Imports: 36 Imported by: 1,170

README

BigQuery Go Reference

Example Usage

First create a bigquery.Client to use throughout your application: [snip]:# (bq-1)

c, err := bigquery.NewClient(ctx, "my-project-ID")
if err != nil {
	// TODO: Handle error.
}

Then use that client to interact with the API: [snip]:# (bq-2)

// Construct a query.
q := c.Query(`
    SELECT year, SUM(number)
    FROM [bigquery-public-data:usa_names.usa_1910_2013]
    WHERE name = "William"
    GROUP BY year
    ORDER BY year
`)
// Execute the query.
it, err := q.Read(ctx)
if err != nil {
	// TODO: Handle error.
}
// Iterate through the results.
for {
	var values []bigquery.Value
	err := it.Next(&values)
	if err == iterator.Done {  // from "google.golang.org/api/iterator"
		break
	}
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(values)
}

Documentation

Overview

Package bigquery provides a client for the BigQuery service.

The following assumes a basic familiarity with BigQuery concepts. See https://cloud.google.com/bigquery/docs.

See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package.

Creating a Client

To start working with this package, create a client: 

ctx := context.Background()
client, err := bigquery.NewClient(ctx, projectID)
if err != nil {
    // TODO: Handle error.
}

Querying

To query existing tables, create a Query and call its Read method: 

q := client.Query(`
    SELECT year, SUM(number) as num
    FROM ` + "`bigquery-public-data.usa_names.usa_1910_2013`" + `
    WHERE name = "William"
    GROUP BY year
    ORDER BY year
`)
it, err := q.Read(ctx)
if err != nil {
    // TODO: Handle error.
}

Then iterate through the resulting rows. You can store a row using anything that implements the ValueLoader interface, or with a slice or map of bigquery.Value. A slice is simplest: 

for {
    var values []bigquery.Value
    err := it.Next(&values)
    if err == iterator.Done {
        break
    }
    if err != nil {
        // TODO: Handle error.
    }
    fmt.Println(values)
}

You can also use a struct whose exported fields match the query: 

type Count struct {
    Year int
    Num  int
}
for {
    var c Count
    err := it.Next(&c)
    if err == iterator.Done {
        break
    }
    if err != nil {
        // TODO: Handle error.
    }
    fmt.Println(c)
}

You can also start the query running and get the results later. Create the query as above, but call Run instead of Read. This returns a Job, which represents an asynchronous operation. 

job, err := q.Run(ctx)
if err != nil {
    // TODO: Handle error.
}

Get the job's ID, a printable string. You can save this string to retrieve the results at a later time, even in another process. 

jobID := job.ID()
fmt.Printf("The job ID is %s\n", jobID)

To retrieve the job's results from the ID, first look up the Job: 

job, err = client.JobFromID(ctx, jobID)
if err != nil {
    // TODO: Handle error.
}

Use the Job.Read method to obtain an iterator, and loop over the rows. Query.Read is just a convenience method that combines Query.Run and Job.Read. 

it, err = job.Read(ctx)
if err != nil {
    // TODO: Handle error.
}
// Proceed with iteration as above.

Datasets and Tables

You can refer to datasets in the client's project with the Dataset method, and in other projects with the DatasetInProject method: 

myDataset := client.Dataset("my_dataset")
yourDataset := client.DatasetInProject("your-project-id", "your_dataset")

These methods create references to datasets, not the datasets themselves. You can have a dataset reference even if the dataset doesn't exist yet. Use Dataset.Create to create a dataset from a reference: 

if err := myDataset.Create(ctx, nil); err != nil {
    // TODO: Handle error.
}

You can refer to tables with Dataset.Table. Like bigquery.Dataset, bigquery.Table is a reference to an object in BigQuery that may or may not exist. 

table := myDataset.Table("my_table")

You can create, delete and update the metadata of tables with methods on Table. For instance, you could create a temporary table with: 

err = myDataset.Table("temp").Create(ctx, &bigquery.TableMetadata{
    ExpirationTime: time.Now().Add(1*time.Hour)})
if err != nil {
    // TODO: Handle error.
}

We'll see how to create a table with a schema in the next section.

Schemas

There are two ways to construct schemas with this package. You can build a schema by hand, like so: 

schema1 := bigquery.Schema{
    {Name: "Name", Required: true, Type: bigquery.StringFieldType},
    {Name: "Grades", Repeated: true, Type: bigquery.IntegerFieldType},
    {Name: "Optional", Required: false, Type: bigquery.IntegerFieldType},
}

Or you can infer the schema from a struct: 

type student struct {
    Name   string
    Grades []int
    Optional bigquery.NullInt64
}
schema2, err := bigquery.InferSchema(student{})
if err != nil {
    // TODO: Handle error.
}
// schema1 and schema2 are identical.

Struct inference supports tags like those of the encoding/json package, so you can change names, ignore fields, or mark a field as nullable (non-required). Fields declared as one of the Null types (NullInt64, NullFloat64, NullString, NullBool, NullTimestamp, NullDate, NullTime, NullDateTime, and NullGeography) are automatically inferred as nullable, so the "nullable" tag is only needed for []byte, *big.Rat and pointer-to-struct fields. 

type student2 struct {
    Name     string `bigquery:"full_name"`
    Grades   []int
    Secret   string `bigquery:"-"`
    Optional []byte `bigquery:",nullable"`
}
schema3, err := bigquery.InferSchema(student2{})
if err != nil {
    // TODO: Handle error.
}
// schema3 has required fields "full_name" and "Grade", and nullable BYTES field "Optional".

Having constructed a schema, you can create a table with it like so: 

if err := table.Create(ctx, &bigquery.TableMetadata{Schema: schema1}); err != nil {
    // TODO: Handle error.
}

Copying

You can copy one or more tables to another table. Begin by constructing a Copier describing the copy. Then set any desired copy options, and finally call Run to get a Job: 

copier := myDataset.Table("dest").CopierFrom(myDataset.Table("src"))
copier.WriteDisposition = bigquery.WriteTruncate
job, err = copier.Run(ctx)
if err != nil {
    // TODO: Handle error.
}

You can chain the call to Run if you don't want to set options: 

job, err = myDataset.Table("dest").CopierFrom(myDataset.Table("src")).Run(ctx)
if err != nil {
    // TODO: Handle error.
}

You can wait for your job to complete: 

status, err := job.Wait(ctx)
if err != nil {
    // TODO: Handle error.
}

Job.Wait polls with exponential backoff. You can also poll yourself, if you wish: 

for {
    status, err := job.Status(ctx)
    if err != nil {
        // TODO: Handle error.
    }
    if status.Done() {
        if status.Err() != nil {
            log.Fatalf("Job failed with error %v", status.Err())
        }
        break
    }
    time.Sleep(pollInterval)
}

Loading and Uploading

There are two ways to populate a table with this package: load the data from a Google Cloud Storage object, or upload rows directly from your program.

For loading, first create a GCSReference, configuring it if desired. Then make a Loader, optionally configure it as well, and call its Run method. 

gcsRef := bigquery.NewGCSReference("gs://my-bucket/my-object")
gcsRef.AllowJaggedRows = true
loader := myDataset.Table("dest").LoaderFrom(gcsRef)
loader.CreateDisposition = bigquery.CreateNever
job, err = loader.Run(ctx)
// Poll the job for completion if desired, as above.

To upload, first define a type that implements the ValueSaver interface, which has a single method named Save. Then create an Inserter, and call its Put method with a slice of values. 

u := table.Inserter()
// Item implements the ValueSaver interface.
items := []*Item{
    {Name: "n1", Size: 32.6, Count: 7},
    {Name: "n2", Size: 4, Count: 2},
    {Name: "n3", Size: 101.5, Count: 1},
}
if err := u.Put(ctx, items); err != nil {
    // TODO: Handle error.
}

You can also upload a struct that doesn't implement ValueSaver. Use the StructSaver type to specify the schema and insert ID by hand, or just supply the struct or struct pointer directly and the schema will be inferred: 

type Item2 struct {
    Name  string
    Size  float64
    Count int
}
// Item implements the ValueSaver interface.
items2 := []*Item2{
    {Name: "n1", Size: 32.6, Count: 7},
    {Name: "n2", Size: 4, Count: 2},
    {Name: "n3", Size: 101.5, Count: 1},
}
if err := u.Put(ctx, items2); err != nil {
    // TODO: Handle error.
}

BigQuery allows for higher throughput when omitting insertion IDs. To enable this, specify the sentinel `NoDedupeID` value for the insertion ID when implementing a ValueSaver.

Extracting

If you've been following so far, extracting data from a BigQuery table into a Google Cloud Storage object will feel familiar. First create an Extractor, then optionally configure it, and lastly call its Run method. 

extractor := table.ExtractorTo(gcsRef)
extractor.DisableHeader = true
job, err = extractor.Run(ctx)
// Poll the job for completion if desired, as above.

Errors

Errors returned by this client are often of the type googleapi.Error: https://godoc.org/google.golang.org/api/googleapi#Error

These errors can be introspected for more information by using `xerrors.As` with the richer *googleapi.Error type. For example: 

	var e *googleapi.Error
	if ok := xerrors.As(err, &e); ok {
		  if e.Code == 409 { ... }
    }

In some cases, your client may received unstructured googleapi.Error error responses. In such cases, it is likely that you have exceeded BigQuery request limits, documented at: https://cloud.google.com/bigquery/quotas

Index

Examples

Constants

View Source 
const (
	// NumericPrecisionDigits is the maximum number of digits in a NUMERIC value.
	NumericPrecisionDigits = 38

	// NumericScaleDigits is the maximum number of digits after the decimal point in a NUMERIC value.
	NumericScaleDigits = 9

	// BigNumericPrecisionDigits is the maximum number of full digits in a BIGNUMERIC value.
	BigNumericPrecisionDigits = 76

	// BigNumericScaleDigits is the maximum number of full digits in a BIGNUMERIC value.
	BigNumericScaleDigits = 38
)
View Source 
const DetectProjectID = "*detect-project-id*"

DetectProjectID is a sentinel value that instructs NewClient to detect the project ID. It is given in place of the projectID argument. NewClient will use the project ID from the given credentials or the default credentials (https://developers.google.com/accounts/docs/application-default-credentials) if no credentials were provided. When providing credentials, not all options will allow NewClient to extract the project ID. Specifically a JWT does not have the project ID encoded.

View Source 
const NoDedupeID = "NoDedupeID"

NoDedupeID indicates a streaming insert row wants to opt out of best-effort deduplication. It is EXPERIMENTAL and subject to change or removal without notice.

View Source 
const (
	// Scope is the Oauth2 scope for the service.
	// For relevant BigQuery scopes, see:
	// https://developers.google.com/identity/protocols/googlescopes#bigqueryv2
	Scope = "https://www.googleapis.com/auth/bigquery"
)

Variables

View Source 
var NeverExpire = time.Time{}.Add(-1)

NeverExpire is a sentinel value used to remove a table'e expiration time.

Functions

func BigNumericString added in v1.14.0 

func BigNumericString(r *big.Rat) string

BigNumericString returns a string representing a *big.Rat in a format compatible with BigQuery SQL. It returns a floating point literal with 38 digits after the decimal point.

func CivilDateTimeString 

func CivilDateTimeString(dt civil.DateTime) string

CivilDateTimeString returns a string representing a civil.DateTime in a format compatible with BigQuery SQL. It separate the date and time with a space, and formats the time with CivilTimeString.

Use CivilDateTimeString when using civil.DateTime in DML, for example in INSERT statements.

func CivilTimeString 

func CivilTimeString(t civil.Time) string

CivilTimeString returns a string representing a civil.Time in a format compatible with BigQuery SQL. It rounds the time to the nearest microsecond and returns a string with six digits of sub-second precision.

Use CivilTimeString when using civil.Time in DML, for example in INSERT statements.

func IntervalString added in v1.32.0 

func IntervalString(iv *IntervalValue) string

IntervalString returns a string representing an *IntervalValue in a format compatible with BigQuery SQL. It returns an interval literal in canonical format.

func NumericString 

func NumericString(r *big.Rat) string

NumericString returns a string representing a *big.Rat in a format compatible with BigQuery SQL. It returns a floating-point literal with 9 digits after the decimal point.

func Seed 

func Seed(s int64)

Seed seeds this package's random number generator, used for generating job and insert IDs. Use Seed to obtain repeatable, deterministic behavior from bigquery clients. Seed should be called before any clients are created.

Types

type AccessEntry 

type AccessEntry struct {
	Role       AccessRole          // The role of the entity
	EntityType EntityType          // The type of entity
	Entity     string              // The entity (individual or group) granted access
	View       *Table              // The view granted access (EntityType must be ViewEntity)
	Routine    *Routine            // The routine granted access (only UDF currently supported)
	Dataset    *DatasetAccessEntry // The resources within a dataset granted access.
}

An AccessEntry describes the permissions that an entity has on a dataset.

type AccessRole 

type AccessRole string

AccessRole is the level of access to grant to a dataset. 

const (
	// OwnerRole is the OWNER AccessRole.
	OwnerRole AccessRole = "OWNER"
	// ReaderRole is the READER AccessRole.
	ReaderRole AccessRole = "READER"
	// WriterRole is the WRITER AccessRole.
	WriterRole AccessRole = "WRITER"
)

type AvroOptions added in v1.25.0 

type AvroOptions struct {
	// UseAvroLogicalTypes indicates whether to interpret logical types as the
	// corresponding BigQuery data type (for example, TIMESTAMP), instead of using
	// the raw type (for example, INTEGER).
	UseAvroLogicalTypes bool
}

AvroOptions are additional options for Avro external data data sources.

type BIEngineReason added in v1.25.0 

type BIEngineReason struct {
	// High-Level BI engine reason for partial or disabled acceleration.
	Code string

	// Human-readable reason for partial or disabled acceleration.
	Message string
}

BIEngineReason contains more detailed information about why a query wasn't fully accelerated.

type BIEngineStatistics added in v1.25.0 

type BIEngineStatistics struct {
	// Specifies which mode of BI Engine acceleration was performed.
	BIEngineMode string

	// In case of DISABLED or PARTIAL BIEngineMode, these
	// contain the explanatory reasons as to why BI Engine could not
	// accelerate. In case the full query was accelerated, this field is not
	// populated.
	BIEngineReasons []*BIEngineReason
}

BIEngineStatistics contains query statistics specific to the use of BI Engine.

type BigtableColumn 

type BigtableColumn struct {
	// Qualifier of the column. Columns in the parent column family that have this
	// exact qualifier are exposed as . field. The column field name is the
	// same as the column qualifier.
	Qualifier string

	// If the qualifier is not a valid BigQuery field identifier i.e. does not match
	// [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field
	// name and is used as field name in queries.
	FieldName string

	// If true, only the latest version of values are exposed for this column.
	// See BigtableColumnFamily.OnlyReadLatest.
	OnlyReadLatest bool

	// The encoding of the values when the type is not STRING.
	// See BigtableColumnFamily.Encoding
	Encoding string

	// The type to convert the value in cells of this column.
	// See BigtableColumnFamily.Type
	Type string
}

BigtableColumn describes how BigQuery should access a Bigtable column.

type BigtableColumnFamily 

type BigtableColumnFamily struct {
	// Identifier of the column family.
	FamilyID string

	// Lists of columns that should be exposed as individual fields as opposed to a
	// list of (column name, value) pairs. All columns whose qualifier matches a
	// qualifier in this list can be accessed as .. Other columns can be accessed as
	// a list through .Column field.
	Columns []*BigtableColumn

	// The encoding of the values when the type is not STRING. Acceptable encoding values are:
	// - TEXT - indicates values are alphanumeric text strings.
	// - BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions.
	// This can be overridden for a specific column by listing that column in 'columns' and
	// specifying an encoding for it.
	Encoding string

	// If true, only the latest version of values are exposed for all columns in this
	// column family. This can be overridden for a specific column by listing that
	// column in 'columns' and specifying a different setting for that column.
	OnlyReadLatest bool

	// The type to convert the value in cells of this
	// column family. The values are expected to be encoded using HBase
	// Bytes.toBytes function when using the BINARY encoding value.
	// Following BigQuery types are allowed (case-sensitive):
	// BYTES STRING INTEGER FLOAT BOOLEAN.
	// The default type is BYTES. This can be overridden for a specific column by
	// listing that column in 'columns' and specifying a type for it.
	Type string
}

BigtableColumnFamily describes how BigQuery should access a Bigtable column family.

type BigtableOptions 

type BigtableOptions struct {
	// A list of column families to expose in the table schema along with their
	// types. If omitted, all column families are present in the table schema and
	// their values are read as BYTES.
	ColumnFamilies []*BigtableColumnFamily

	// If true, then the column families that are not specified in columnFamilies
	// list are not exposed in the table schema. Otherwise, they are read with BYTES
	// type values. The default is false.
	IgnoreUnspecifiedColumnFamilies bool

	// If true, then the rowkey column families will be read and converted to string.
	// Otherwise they are read with BYTES type values and users need to manually cast
	// them with CAST if necessary. The default is false.
	ReadRowkeyAsString bool
}

BigtableOptions are additional options for Bigtable external data sources.

type CSVOptions 

type CSVOptions struct {
	// AllowJaggedRows causes missing trailing optional columns to be tolerated
	// when reading CSV data. Missing values are treated as nulls.
	AllowJaggedRows bool

	// AllowQuotedNewlines sets whether quoted data sections containing
	// newlines are allowed when reading CSV data.
	AllowQuotedNewlines bool

	// Encoding is the character encoding of data to be read.
	Encoding Encoding

	// FieldDelimiter is the separator for fields in a CSV file, used when
	// reading or exporting data. The default is ",".
	FieldDelimiter string

	// Quote is the value used to quote data sections in a CSV file. The
	// default quotation character is the double quote ("), which is used if
	// both Quote and ForceZeroQuote are unset.
	// To specify that no character should be interpreted as a quotation
	// character, set ForceZeroQuote to true.
	// Only used when reading data.
	Quote          string
	ForceZeroQuote bool

	// The number of rows at the top of a CSV file that BigQuery will skip when
	// reading data.
	SkipLeadingRows int64

	// An optional custom string that will represent a NULL
	// value in CSV import data.
	NullMarker string

	// Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table,
	// from '\\x00' to '\\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
	PreserveASCIIControlCharacters bool
}

CSVOptions are additional options for CSV external data sources.

type Client 

type Client struct {
	// Location, if set, will be used as the default location for all subsequent
	// dataset creation and job operations. A location specified directly in one of
	// those operations will override this value.
	Location string
	// contains filtered or unexported fields
}

Client may be used to perform BigQuery operations.

func NewClient 

func NewClient(ctx context.Context, projectID string, opts ...option.ClientOption) (*Client, error)

NewClient constructs a new Client which can perform BigQuery operations. Operations performed via the client are billed to the specified GCP project.

If the project ID is set to DetectProjectID, NewClient will attempt to detect the project ID from credentials.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	_ = client // TODO: Use client.
}

Output:

func (*Client) Close 

func (c *Client) Close() error

Close closes any resources held by the client. Close should be called when the client is no longer needed. It need not be called at program exit.

func (*Client) Dataset 

func (c *Client) Dataset(id string) *Dataset

Dataset creates a handle to a BigQuery dataset in the client's project.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ds := client.Dataset("my_dataset")
	fmt.Println(ds)
}

Output:

func (*Client) DatasetInProject 

func (c *Client) DatasetInProject(projectID, datasetID string) *Dataset

DatasetInProject creates a handle to a BigQuery dataset in the specified project.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ds := client.DatasetInProject("their-project-id", "their-dataset")
	fmt.Println(ds)
}

Output:

func (*Client) Datasets 

func (c *Client) Datasets(ctx context.Context) *DatasetIterator

Datasets returns an iterator over the datasets in a project. The Client's project is used by default, but that can be changed by setting ProjectID on the returned iterator before calling Next.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	it := client.Datasets(ctx)
	_ = it // TODO: iterate using Next or iterator.Pager.
}

Output:

func (*Client) DatasetsInProject deprecated 

func (c *Client) DatasetsInProject(ctx context.Context, projectID string) *DatasetIterator

DatasetsInProject returns an iterator over the datasets in the provided project.

Deprecated: call Client.Datasets, then set ProjectID on the returned iterator.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	it := client.DatasetsInProject(ctx, "their-project-id")
	_ = it // TODO: iterate using Next or iterator.Pager.
}

Output:

func (*Client) JobFromID 

func (c *Client) JobFromID(ctx context.Context, id string) (*Job, error)

JobFromID creates a Job which refers to an existing BigQuery job. The job need not have been created by this package. For example, the job may have been created in the BigQuery console.

For jobs whose location is other than "US" or "EU", set Client.Location or use JobFromIDLocation.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func getJobID() string { return "" }

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	jobID := getJobID() // Get a job ID using Job.ID, the console or elsewhere.
	job, err := client.JobFromID(ctx, jobID)
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(job.LastStatus()) // Display the job's status.
}

Output:

func (*Client) JobFromIDLocation 

func (c *Client) JobFromIDLocation(ctx context.Context, id, location string) (j *Job, err error)

JobFromIDLocation creates a Job which refers to an existing BigQuery job. The job need not have been created by this package (for example, it may have been created in the BigQuery console), but it must exist in the specified location.

func (*Client) JobFromProject added in v1.25.0 

func (c *Client) JobFromProject(ctx context.Context, projectID, jobID, location string) (j *Job, err error)

JobFromProject creates a Job which refers to an existing BigQuery job. The job need not have been created by this package, nor does it need to reside within the same project or location as the instantiated client.

func (*Client) Jobs 

func (c *Client) Jobs(ctx context.Context) *JobIterator

Jobs lists jobs within a project.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	it := client.Jobs(ctx)
	it.State = bigquery.Running // list only running jobs.
	_ = it                      // TODO: iterate using Next or iterator.Pager.
}

Output:

func (*Client) Project added in v1.19.0 

func (c *Client) Project() string

Project returns the project ID or number for this instance of the client, which may have either been explicitly specified or autodetected.

func (*Client) Query 

func (c *Client) Query(q string) *Query

Query creates a query with string q. The returned Query may optionally be further configured before its Run method is called.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	q := client.Query("select name, num from t1")
	q.DefaultProjectID = "project-id"
	// TODO: set other options on the Query.
	// TODO: Call Query.Run or Query.Read.
}

Output:
Example (EncryptionKey)

This example demonstrates how to run a query job on a table with a customer-managed encryption key. The same applies to load and copy jobs as well. 

package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	q := client.Query("select name, num from t1")
	// TODO: Replace this key with a key you have created in Cloud KMS.
	keyName := "projects/P/locations/L/keyRings/R/cryptoKeys/K"
	q.DestinationEncryptionConfig = &bigquery.EncryptionConfig{KMSKeyName: keyName}
	// TODO: set other options on the Query.
	// TODO: Call Query.Run or Query.Read.
}

Output:
Example (Parameters) 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	q := client.Query("select num from t1 where name = @user")
	q.Parameters = []bigquery.QueryParameter{
		{Name: "user", Value: "Elizabeth"},
	}
	// TODO: set other options on the Query.
	// TODO: Call Query.Run or Query.Read.
}

Output:

type CloneDefinition added in v1.31.0 

type CloneDefinition struct {

	// BaseTableReference describes the ID of the table that this clone
	// came from.
	BaseTableReference *Table

	// CloneTime indicates when the base table was cloned.
	CloneTime time.Time
}

CloneDefinition provides metadata related to the origin of a clone.

type Clustering 

type Clustering struct {
	Fields []string
}

Clustering governs the organization of data within a managed table. For more information, see https://cloud.google.com/bigquery/docs/clustered-tables

type Compression 

type Compression string

Compression is the type of compression to apply when writing data to Google Cloud Storage. 

const (
	// None specifies no compression.
	None Compression = "NONE"
	// Gzip specifies gzip compression.
	Gzip Compression = "GZIP"
	// Deflate specifies DEFLATE compression for Avro files.
	Deflate Compression = "DEFLATE"
	// Snappy specifies SNAPPY compression for Avro files.
	Snappy Compression = "SNAPPY"
)

type ConnectionProperty added in v1.23.0 

type ConnectionProperty struct {
	// Name of the connection property to set.
	Key string
	// Value of the connection property.
	Value string
}

ConnectionProperty represents a single key and value pair that can be sent alongside a query request.

type Copier 

type Copier struct {
	JobIDConfig
	CopyConfig
	// contains filtered or unexported fields
}

A Copier copies data into a BigQuery table from one or more BigQuery tables.

func (*Copier) Run 

func (c *Copier) Run(ctx context.Context) (*Job, error)

Run initiates a copy job.

type CopyConfig 

type CopyConfig struct {
	// Srcs are the tables from which data will be copied.
	Srcs []*Table

	// Dst is the table into which the data will be copied.
	Dst *Table

	// CreateDisposition specifies the circumstances under which the destination table will be created.
	// The default is CreateIfNeeded.
	CreateDisposition TableCreateDisposition

	// WriteDisposition specifies how existing data in the destination table is treated.
	// The default is WriteEmpty.
	WriteDisposition TableWriteDisposition

	// The labels associated with this job.
	Labels map[string]string

	// Custom encryption configuration (e.g., Cloud KMS keys).
	DestinationEncryptionConfig *EncryptionConfig

	// One of the supported operation types when executing a Table Copy jobs.  By default this
	// copies tables, but can also be set to perform snapshot or restore operations.
	OperationType TableCopyOperationType

	// Sets a best-effort deadline on a specific job.  If job execution exceeds this
	// timeout, BigQuery may attempt to cancel this work automatically.
	//
	// This deadline cannot be adjusted or removed once the job is created.  Consider
	// using Job.Cancel in situations where you need more dynamic behavior.
	//
	// Experimental: this option is experimental and may be modified or removed in future versions,
	// regardless of any other documented package stability guarantees.
	JobTimeout time.Duration
}

CopyConfig holds the configuration for a copy job.

type DMLStatistics added in v1.20.1 

type DMLStatistics struct {
	// Rows added by the statement.
	InsertedRowCount int64
	// Rows removed by the statement.
	DeletedRowCount int64
	// Rows changed by the statement.
	UpdatedRowCount int64
}

DMLStatistics contains counts of row mutations triggered by a DML query statement.

type DataFormat 

type DataFormat string

DataFormat describes the format of BigQuery table data. 

const (
	CSV             DataFormat = "CSV"
	Avro            DataFormat = "AVRO"
	JSON            DataFormat = "NEWLINE_DELIMITED_JSON"
	DatastoreBackup DataFormat = "DATASTORE_BACKUP"
	GoogleSheets    DataFormat = "GOOGLE_SHEETS"
	Bigtable        DataFormat = "BIGTABLE"
	Parquet         DataFormat = "PARQUET"
	ORC             DataFormat = "ORC"
	// For BQ ML Models, TensorFlow Saved Model format.
	TFSavedModel DataFormat = "ML_TF_SAVED_MODEL"
	// For BQ ML Models, xgBoost Booster format.
	XGBoostBooster DataFormat = "ML_XGBOOST_BOOSTER"
)

Constants describing the format of BigQuery table data.

type Dataset 

type Dataset struct {
	ProjectID string
	DatasetID string
	// contains filtered or unexported fields
}

Dataset is a reference to a BigQuery dataset.

func (*Dataset) Create 

func (d *Dataset) Create(ctx context.Context, md *DatasetMetadata) (err error)

Create creates a dataset in the BigQuery service. An error will be returned if the dataset already exists. Pass in a DatasetMetadata value to configure the dataset.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ds := client.Dataset("my_dataset")
	if err := ds.Create(ctx, &bigquery.DatasetMetadata{Location: "EU"}); err != nil {
		// TODO: Handle error.
	}
}

Output:

func (*Dataset) Delete 

func (d *Dataset) Delete(ctx context.Context) (err error)

Delete deletes the dataset. Delete will fail if the dataset is not empty.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	if err := client.Dataset("my_dataset").Delete(ctx); err != nil {
		// TODO: Handle error.
	}
}

Output:

func (*Dataset) DeleteWithContents 

func (d *Dataset) DeleteWithContents(ctx context.Context) (err error)

DeleteWithContents deletes the dataset, as well as contained resources.

func (*Dataset) Identifier added in v1.25.0 

func (d *Dataset) Identifier(f IdentifierFormat) (string, error)

Identifier returns the ID of the dataset in the requested format.

For Standard SQL format, the identifier will be quoted if the ProjectID contains dash (-) characters.

func (*Dataset) Metadata 

func (d *Dataset) Metadata(ctx context.Context) (md *DatasetMetadata, err error)

Metadata fetches the metadata for the dataset.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	md, err := client.Dataset("my_dataset").Metadata(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(md)
}

Output:

func (*Dataset) Model 

func (d *Dataset) Model(modelID string) *Model

Model creates a handle to a BigQuery model in the dataset. To determine if a model exists, call Model.Metadata. If the model does not already exist, you can create it via execution of a CREATE MODEL query.

func (*Dataset) Models 

func (d *Dataset) Models(ctx context.Context) *ModelIterator

Models returns an iterator over the models in the Dataset.

func (*Dataset) Routine 

func (d *Dataset) Routine(routineID string) *Routine

Routine creates a handle to a BigQuery routine in the dataset. To determine if a routine exists, call Routine.Metadata.

func (*Dataset) Routines 

func (d *Dataset) Routines(ctx context.Context) *RoutineIterator

Routines returns an iterator over the routines in the Dataset.

func (*Dataset) Table 

func (d *Dataset) Table(tableID string) *Table

Table creates a handle to a BigQuery table in the dataset. To determine if a table exists, call Table.Metadata. If the table does not already exist, use Table.Create to create it.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	// Table creates a reference to the table. It does not create the actual
	// table in BigQuery; to do so, use Table.Create.
	t := client.Dataset("my_dataset").Table("my_table")
	fmt.Println(t)
}

Output:

func (*Dataset) Tables 

func (d *Dataset) Tables(ctx context.Context) *TableIterator

Tables returns an iterator over the tables in the Dataset.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	it := client.Dataset("my_dataset").Tables(ctx)
	_ = it // TODO: iterate using Next or iterator.Pager.
}

Output:

func (*Dataset) Update 

func (d *Dataset) Update(ctx context.Context, dm DatasetMetadataToUpdate, etag string) (md *DatasetMetadata, err error)

Update modifies specific Dataset metadata fields. To perform a read-modify-write that protects against intervening reads, set the etag argument to the DatasetMetadata.ETag field from the read. Pass the empty string for etag for a "blind write" that will always succeed.

Example (BlindWrite)

To perform a blind write, ignoring the existing state (and possibly overwriting other updates), pass the empty string as the etag. 

package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	md, err := client.Dataset("my_dataset").Update(ctx, bigquery.DatasetMetadataToUpdate{Name: "blind"}, "")
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(md)
}

Output:
Example (ReadModifyWrite)

This example illustrates how to perform a read-modify-write sequence on dataset metadata. Passing the metadata's ETag to the Update call ensures that the call will fail if the metadata was changed since the read. 

package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ds := client.Dataset("my_dataset")
	md, err := ds.Metadata(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	md2, err := ds.Update(ctx,
		bigquery.DatasetMetadataToUpdate{Name: "new " + md.Name},
		md.ETag)
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(md2)
}

Output:

type DatasetAccessEntry added in v1.30.0 

type DatasetAccessEntry struct {
	// The dataset to which this entry applies.
	Dataset *Dataset
	// The list of target types within the dataset
	// to which this entry applies.
	//
	// Current supported values:
	//
	// VIEWS - This entry applies to views in the dataset.
	TargetTypes []string
}

DatasetAccessEntry is an access entry that refers to resources within another dataset.

type DatasetIterator 

type DatasetIterator struct {
	// ListHidden causes hidden datasets to be listed when set to true.
	// Set before the first call to Next.
	ListHidden bool

	// Filter restricts the datasets returned by label. The filter syntax is described in
	// https://cloud.google.com/bigquery/docs/labeling-datasets#filtering_datasets_using_labels
	// Set before the first call to Next.
	Filter string

	// The project ID of the listed datasets.
	// Set before the first call to Next.
	ProjectID string
	// contains filtered or unexported fields
}

DatasetIterator iterates over the datasets in a project.

func (*DatasetIterator) Next 

func (it *DatasetIterator) Next() (*Dataset, error)

Next returns the next Dataset. Its second return value is iterator.Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
	"google.golang.org/api/iterator"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	it := client.Datasets(ctx)
	for {
		ds, err := it.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			// TODO: Handle error.
		}
		fmt.Println(ds)
	}
}

Output:

func (*DatasetIterator) PageInfo 

func (it *DatasetIterator) PageInfo() *iterator.PageInfo

PageInfo supports pagination. See the google.golang.org/api/iterator package for details.

type DatasetMetadata 

type DatasetMetadata struct {
	// These fields can be set when creating a dataset.
	Name                    string            // The user-friendly name for this dataset.
	Description             string            // The user-friendly description of this dataset.
	Location                string            // The geo location of the dataset.
	DefaultTableExpiration  time.Duration     // The default expiration time for new tables.
	Labels                  map[string]string // User-provided labels.
	Access                  []*AccessEntry    // Access permissions.
	DefaultEncryptionConfig *EncryptionConfig

	// These fields are read-only.
	CreationTime     time.Time
	LastModifiedTime time.Time // When the dataset or any of its tables were modified.
	FullID           string    // The full dataset ID in the form projectID:datasetID.

	// The tags associated with this dataset. Tag keys are
	// globally unique, and managed via the resource manager API.
	// More information: https://cloud.google.com/resource-manager/docs/tags/tags-overview
	Tags []*DatasetTag

	// ETag is the ETag obtained when reading metadata. Pass it to Dataset.Update to
	// ensure that the metadata hasn't changed since it was read.
	ETag string
}

DatasetMetadata contains information about a BigQuery dataset.

type DatasetMetadataToUpdate 

type DatasetMetadataToUpdate struct {
	Description optional.String // The user-friendly description of this table.
	Name        optional.String // The user-friendly name for this dataset.

	// DefaultTableExpiration is the default expiration time for new tables.
	// If set to time.Duration(0), new tables never expire.
	DefaultTableExpiration optional.Duration

	// DefaultEncryptionConfig defines CMEK settings for new resources created
	// in the dataset.
	DefaultEncryptionConfig *EncryptionConfig

	// The entire access list. It is not possible to replace individual entries.
	Access []*AccessEntry
	// contains filtered or unexported fields
}

DatasetMetadataToUpdate is used when updating a dataset's metadata. Only non-nil fields will be updated.

func (*DatasetMetadataToUpdate) DeleteLabel 

func (u *DatasetMetadataToUpdate) DeleteLabel(name string)

DeleteLabel causes a label to be deleted on a call to Update.

func (*DatasetMetadataToUpdate) SetLabel 

func (u *DatasetMetadataToUpdate) SetLabel(name, value string)

SetLabel causes a label to be added or modified on a call to Update.

type DatasetTag added in v1.33.0 

type DatasetTag struct {
	// TagKey is the namespaced friendly name of the tag key, e.g.
	// "12345/environment" where 12345 is org id.
	TagKey string

	// TagValue is the friendly short name of the tag value, e.g.
	// "production".
	TagValue string
}

DatasetTag is a representation of a single tag key/value.

type DecimalTargetType added in v1.20.1 

type DecimalTargetType string

DecimalTargetType is used to express preference ordering for converting values from external formats. 

var (
	// NumericTargetType indicates the preferred type is NUMERIC when supported.
	NumericTargetType DecimalTargetType = "NUMERIC"

	// BigNumericTargetType indicates the preferred type is BIGNUMERIC when supported.
	BigNumericTargetType DecimalTargetType = "BIGNUMERIC"

	// StringTargetType indicates the preferred type is STRING when supported.
	StringTargetType DecimalTargetType = "STRING"
)

type Encoding 

type Encoding string

Encoding specifies the character encoding of data to be loaded into BigQuery. See https://cloud.google.com/bigquery/docs/reference/v2/jobs#configuration.load.encoding for more details about how this is used. 

const (
	// UTF_8 specifies the UTF-8 encoding type.
	UTF_8 Encoding = "UTF-8"
	// ISO_8859_1 specifies the ISO-8859-1 encoding type.
	ISO_8859_1 Encoding = "ISO-8859-1"
)

type EncryptionConfig 

type EncryptionConfig struct {
	// Describes the Cloud KMS encryption key that will be used to protect
	// destination BigQuery table. The BigQuery Service Account associated with your
	// project requires access to this encryption key.
	KMSKeyName string
}

EncryptionConfig configures customer-managed encryption on tables and ML models.

type EntityType 

type EntityType int

EntityType is the type of entity in an AccessEntry. 

const (
	// DomainEntity is a domain (e.g. "example.com").
	DomainEntity EntityType = iota + 1

	// GroupEmailEntity is an email address of a Google Group.
	GroupEmailEntity

	// UserEmailEntity is an email address of an individual user.
	UserEmailEntity

	// SpecialGroupEntity is a special group: one of projectOwners, projectReaders, projectWriters or
	// allAuthenticatedUsers.
	SpecialGroupEntity

	// ViewEntity is a BigQuery logical view.
	ViewEntity

	// IAMMemberEntity represents entities present in IAM but not represented using
	// the other entity types.
	IAMMemberEntity

	// RoutineEntity is a BigQuery routine, referencing a User Defined Function (UDF).
	RoutineEntity

	// DatasetEntity is BigQuery dataset, present in the access list.
	DatasetEntity
)

type Error 

type Error struct {
	// Mirrors bq.ErrorProto, but drops DebugInfo
	Location, Message, Reason string
}

An Error contains detailed information about a failed bigquery operation. Detailed description of possible Reasons can be found here: https://cloud.google.com/bigquery/troubleshooting-errors.

func (Error) Error 

func (e Error) Error() string

type ExplainQueryStage 

type ExplainQueryStage struct {
	// CompletedParallelInputs: Number of parallel input segments completed.
	CompletedParallelInputs int64

	// ComputeAvg: Duration the average shard spent on CPU-bound tasks.
	ComputeAvg time.Duration

	// ComputeMax: Duration the slowest shard spent on CPU-bound tasks.
	ComputeMax time.Duration

	// Relative amount of the total time the average shard spent on CPU-bound tasks.
	ComputeRatioAvg float64

	// Relative amount of the total time the slowest shard spent on CPU-bound tasks.
	ComputeRatioMax float64

	// EndTime: Stage end time.
	EndTime time.Time

	// Unique ID for stage within plan.
	ID int64

	// InputStages: IDs for stages that are inputs to this stage.
	InputStages []int64

	// Human-readable name for stage.
	Name string

	// ParallelInputs: Number of parallel input segments to be processed.
	ParallelInputs int64

	// ReadAvg: Duration the average shard spent reading input.
	ReadAvg time.Duration

	// ReadMax: Duration the slowest shard spent reading input.
	ReadMax time.Duration

	// Relative amount of the total time the average shard spent reading input.
	ReadRatioAvg float64

	// Relative amount of the total time the slowest shard spent reading input.
	ReadRatioMax float64

	// Number of records read into the stage.
	RecordsRead int64

	// Number of records written by the stage.
	RecordsWritten int64

	// ShuffleOutputBytes: Total number of bytes written to shuffle.
	ShuffleOutputBytes int64

	// ShuffleOutputBytesSpilled: Total number of bytes written to shuffle
	// and spilled to disk.
	ShuffleOutputBytesSpilled int64

	// StartTime: Stage start time.
	StartTime time.Time

	// Current status for the stage.
	Status string

	// List of operations within the stage in dependency order (approximately
	// chronological).
	Steps []*ExplainQueryStep

	// WaitAvg: Duration the average shard spent waiting to be scheduled.
	WaitAvg time.Duration

	// WaitMax: Duration the slowest shard spent waiting to be scheduled.
	WaitMax time.Duration

	// Relative amount of the total time the average shard spent waiting to be scheduled.
	WaitRatioAvg float64

	// Relative amount of the total time the slowest shard spent waiting to be scheduled.
	WaitRatioMax float64

	// WriteAvg: Duration the average shard spent on writing output.
	WriteAvg time.Duration

	// WriteMax: Duration the slowest shard spent on writing output.
	WriteMax time.Duration

	// Relative amount of the total time the average shard spent on writing output.
	WriteRatioAvg float64

	// Relative amount of the total time the slowest shard spent on writing output.
	WriteRatioMax float64
}

ExplainQueryStage describes one stage of a query.

type ExplainQueryStep 

type ExplainQueryStep struct {
	// Machine-readable operation type.
	Kind string

	// Human-readable stage descriptions.
	Substeps []string
}

ExplainQueryStep describes one step of a query stage.

type ExternalData 

type ExternalData interface {
	// contains filtered or unexported methods
}

ExternalData is a table which is stored outside of BigQuery. It is implemented by *ExternalDataConfig. GCSReference also implements it, for backwards compatibility.

type ExternalDataConfig 

type ExternalDataConfig struct {
	// The format of the data. Required.
	SourceFormat DataFormat

	// The fully-qualified URIs that point to your
	// data in Google Cloud. Required.
	//
	// For Google Cloud Storage URIs, each URI can contain one '*' wildcard character
	// and it must come after the 'bucket' name. Size limits related to load jobs
	// apply to external data sources.
	//
	// For Google Cloud Bigtable URIs, exactly one URI can be specified and it has be
	// a fully specified and valid HTTPS URL for a Google Cloud Bigtable table.
	//
	// For Google Cloud Datastore backups, exactly one URI can be specified. Also,
	// the '*' wildcard character is not allowed.
	SourceURIs []string

	// The schema of the data. Required for CSV and JSON; disallowed for the
	// other formats.
	Schema Schema

	// Try to detect schema and format options automatically.
	// Any option specified explicitly will be honored.
	AutoDetect bool

	// The compression type of the data.
	Compression Compression

	// IgnoreUnknownValues causes values not matching the schema to be
	// tolerated. Unknown values are ignored. For CSV this ignores extra values
	// at the end of a line. For JSON this ignores named values that do not
	// match any column name. If this field is not set, records containing
	// unknown values are treated as bad records. The MaxBadRecords field can
	// be used to customize how bad records are handled.
	IgnoreUnknownValues bool

	// MaxBadRecords is the maximum number of bad records that will be ignored
	// when reading data.
	MaxBadRecords int64

	// Additional options for CSV, GoogleSheets, Bigtable, and Parquet formats.
	Options ExternalDataConfigOptions

	// HivePartitioningOptions allows use of Hive partitioning based on the
	// layout of objects in Google Cloud Storage.
	HivePartitioningOptions *HivePartitioningOptions

	// DecimalTargetTypes allows selection of how decimal values are converted when
	// processed in bigquery, subject to the value type having sufficient precision/scale
	// to support the values.  In the order of NUMERIC, BIGNUMERIC, and STRING, a type is
	// selected if is present in the list and if supports the necessary precision and scale.
	//
	// StringTargetType supports all precision and scale values.
	DecimalTargetTypes []DecimalTargetType

	// ConnectionID associates an external data configuration with a connection ID.
	// Connections are managed through the BigQuery Connection API:
	// https://pkg.go.dev/cloud.google.com/go/bigquery/connection/apiv1
	ConnectionID string
}

ExternalDataConfig describes data external to BigQuery that can be used in queries and to create external tables.

type ExternalDataConfigOptions 

type ExternalDataConfigOptions interface {
	// contains filtered or unexported methods
}

ExternalDataConfigOptions are additional options for external data configurations. This interface is implemented by CSVOptions, GoogleSheetsOptions and BigtableOptions.

type ExtractConfig 

type ExtractConfig struct {
	// Src is the table from which data will be extracted.
	// Only one of Src or SrcModel should be specified.
	Src *Table

	// SrcModel is the ML model from which the data will be extracted.
	// Only one of Src or SrcModel should be specified.
	SrcModel *Model

	// Dst is the destination into which the data will be extracted.
	Dst *GCSReference

	// DisableHeader disables the printing of a header row in exported data.
	DisableHeader bool

	// The labels associated with this job.
	Labels map[string]string

	// For Avro-based extracts, controls whether logical type annotations are generated.
	//
	// Example:  With this enabled, writing a BigQuery TIMESTAMP column will result in
	// an integer column annotated with the appropriate timestamp-micros/millis annotation
	// in the resulting Avro files.
	UseAvroLogicalTypes bool

	// Sets a best-effort deadline on a specific job.  If job execution exceeds this
	// timeout, BigQuery may attempt to cancel this work automatically.
	//
	// This deadline cannot be adjusted or removed once the job is created.  Consider
	// using Job.Cancel in situations where you need more dynamic behavior.
	//
	// Experimental: this option is experimental and may be modified or removed in future versions,
	// regardless of any other documented package stability guarantees.
	JobTimeout time.Duration
}

ExtractConfig holds the configuration for an extract job.

type ExtractStatistics 

type ExtractStatistics struct {
	// The number of files per destination URI or URI pattern specified in the
	// extract configuration. These values will be in the same order as the
	// URIs specified in the 'destinationUris' field.
	DestinationURIFileCounts []int64
}

ExtractStatistics contains statistics about an extract job.

type Extractor 

type Extractor struct {
	JobIDConfig
	ExtractConfig
	// contains filtered or unexported fields
}

An Extractor extracts data from a BigQuery table into Google Cloud Storage.

func (*Extractor) Run 

func (e *Extractor) Run(ctx context.Context) (j *Job, err error)

Run initiates an extract job.

type FieldSchema 

type FieldSchema struct {
	// The field name.
	// Must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_),
	// and must start with a letter or underscore.
	// The maximum length is 128 characters.
	Name string

	// A description of the field. The maximum length is 16,384 characters.
	Description string

	// Whether the field may contain multiple values.
	Repeated bool
	// Whether the field is required.  Ignored if Repeated is true.
	Required bool

	// The field data type.  If Type is Record, then this field contains a nested schema,
	// which is described by Schema.
	Type FieldType

	// Annotations for enforcing column-level security constraints.
	PolicyTags *PolicyTagList

	// Describes the nested schema if Type is set to Record.
	Schema Schema

	// Maximum length of the field for STRING or BYTES type.
	//
	// It is invalid to set value for types other than STRING or BYTES.
	//
	// For STRING type, this represents the maximum UTF-8 length of strings
	// allowed in the field. For BYTES type, this represents the maximum
	// number of bytes in the field.
	MaxLength int64

	// Precision can be used to constrain the maximum number of
	// total digits allowed for NUMERIC or BIGNUMERIC types.
	//
	// It is invalid to set values for Precision for types other than
	// NUMERIC or BIGNUMERIC.
	//
	// For NUMERIC type, acceptable values for Precision must
	// be: 1 ≤ (Precision - Scale) ≤ 29. Values for Scale
	// must be: 0 ≤ Scale ≤ 9.
	//
	// For BIGNUMERIC type, acceptable values for Precision must
	// be: 1 ≤ (Precision - Scale) ≤ 38. Values for Scale
	// must be: 0 ≤ Scale ≤ 38.
	Precision int64

	// Scale can be used to constrain the maximum number of digits
	// in the fractional part of a NUMERIC or BIGNUMERIC type.
	//
	// If the Scale value is set, the Precision value must be set as well.
	//
	// It is invalid to set values for Scale for types other than
	// NUMERIC or BIGNUMERIC.
	//
	// See the Precision field for additional guidance about valid values.
	Scale int64

	// DefaultValueExpression is used to specify the default value of a field
	// using a SQL expression.  It can only be set for top level fields (columns).
	//
	// You can use struct or array expression to specify default value for the
	// entire struct or array. The valid SQL expressions are:
	//
	// - Literals for all data types, including STRUCT and ARRAY.
	// - The following functions:
	//   - CURRENT_TIMESTAMP
	//   - CURRENT_TIME
	//   - CURRENT_DATE
	//   - CURRENT_DATETIME
	//   - GENERATE_UUID
	//   - RAND
	//   - SESSION_USER
	//   - ST_GEOGPOINT
	//   - Struct or array composed with the above allowed functions, for example:
	//       [CURRENT_DATE(), DATE '2020-01-01']"
	DefaultValueExpression string
}

FieldSchema describes a single field.

type FieldType 

type FieldType string

FieldType is the type of field. 

const (
	// StringFieldType is a string field type.
	StringFieldType FieldType = "STRING"
	// BytesFieldType is a bytes field type.
	BytesFieldType FieldType = "BYTES"
	// IntegerFieldType is a integer field type.
	IntegerFieldType FieldType = "INTEGER"
	// FloatFieldType is a float field type.
	FloatFieldType FieldType = "FLOAT"
	// BooleanFieldType is a boolean field type.
	BooleanFieldType FieldType = "BOOLEAN"
	// TimestampFieldType is a timestamp field type.
	TimestampFieldType FieldType = "TIMESTAMP"
	// RecordFieldType is a record field type. It is typically used to create columns with repeated or nested data.
	RecordFieldType FieldType = "RECORD"
	// DateFieldType is a date field type.
	DateFieldType FieldType = "DATE"
	// TimeFieldType is a time field type.
	TimeFieldType FieldType = "TIME"
	// DateTimeFieldType is a datetime field type.
	DateTimeFieldType FieldType = "DATETIME"
	// NumericFieldType is a numeric field type. Numeric types include integer types, floating point types and the
	// NUMERIC data type.
	NumericFieldType FieldType = "NUMERIC"
	// GeographyFieldType is a string field type.  Geography types represent a set of points
	// on the Earth's surface, represented in Well Known Text (WKT) format.
	GeographyFieldType FieldType = "GEOGRAPHY"
	// BigNumericFieldType is a numeric field type that supports values of larger precision
	// and scale than the NumericFieldType.
	BigNumericFieldType FieldType = "BIGNUMERIC"
	// IntervalFieldType is a representation of a duration or an amount of time.
	IntervalFieldType FieldType = "INTERVAL"
	// JSONFieldType is a representation of a json object.
	JSONFieldType FieldType = "JSON"
)

type FileConfig 

type FileConfig struct {
	// SourceFormat is the format of the data to be read.
	// Allowed values are: Avro, CSV, DatastoreBackup, JSON, ORC, and Parquet.  The default is CSV.
	SourceFormat DataFormat

	// Indicates if we should automatically infer the options and
	// schema for CSV and JSON sources.
	AutoDetect bool

	// MaxBadRecords is the maximum number of bad records that will be ignored
	// when reading data.
	MaxBadRecords int64

	// IgnoreUnknownValues causes values not matching the schema to be
	// tolerated. Unknown values are ignored. For CSV this ignores extra values
	// at the end of a line. For JSON this ignores named values that do not
	// match any column name. If this field is not set, records containing
	// unknown values are treated as bad records. The MaxBadRecords field can
	// be used to customize how bad records are handled.
	IgnoreUnknownValues bool

	// Schema describes the data. It is required when reading CSV or JSON data,
	// unless the data is being loaded into a table that already exists.
	Schema Schema

	// Additional options for CSV files.
	CSVOptions

	// Additional options for Parquet files.
	ParquetOptions *ParquetOptions

	// Additional options for Avro files.
	AvroOptions *AvroOptions
}

FileConfig contains configuration options that pertain to files, typically text files that require interpretation to be used as a BigQuery table. A file may live in Google Cloud Storage (see GCSReference), or it may be loaded into a table via the Table.LoaderFromReader.

type GCSReference 

type GCSReference struct {
	// URIs refer to Google Cloud Storage objects.
	URIs []string

	FileConfig

	// DestinationFormat is the format to use when writing exported files.
	// Allowed values are: CSV, Avro, JSON.  The default is CSV.
	// CSV is not supported for tables with nested or repeated fields.
	DestinationFormat DataFormat

	// Compression specifies the type of compression to apply when writing data
	// to Google Cloud Storage, or using this GCSReference as an ExternalData
	// source with CSV or JSON SourceFormat. Default is None.
	//
	// Avro files allow additional compression types: DEFLATE and SNAPPY.
	Compression Compression
}

GCSReference is a reference to one or more Google Cloud Storage objects, which together constitute an input or output to a BigQuery operation.

func NewGCSReference 

func NewGCSReference(uri ...string) *GCSReference

NewGCSReference constructs a reference to one or more Google Cloud Storage objects, which together constitute a data source or destination. In the simple case, a single URI in the form gs://bucket/object may refer to a single GCS object. Data may also be split into mutiple files, if multiple URIs or URIs containing wildcards are provided. Each URI may contain one '*' wildcard character, which (if present) must come after the bucket name. For more information about the treatment of wildcards and multiple URIs, see https://cloud.google.com/bigquery/exporting-data-from-bigquery#exportingmultiple

Example 
package main

import (
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	gcsRef := bigquery.NewGCSReference("gs://my-bucket/my-object")
	fmt.Println(gcsRef)
}

Output:

type GoogleSheetsOptions 

type GoogleSheetsOptions struct {
	// The number of rows at the top of a sheet that BigQuery will skip when
	// reading data.
	SkipLeadingRows int64
	// Optionally specifies a more specific range of cells to include.
	// Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id
	//
	// Example: sheet1!A1:B20
	Range string
}

GoogleSheetsOptions are additional options for GoogleSheets external data sources.

type HivePartitioningMode added in v1.14.0 

type HivePartitioningMode string

HivePartitioningMode is used in conjunction with HivePartitioningOptions. 

const (
	// AutoHivePartitioningMode automatically infers partitioning key and types.
	AutoHivePartitioningMode HivePartitioningMode = "AUTO"
	// StringHivePartitioningMode automatically infers partitioning keys and treats values as string.
	StringHivePartitioningMode HivePartitioningMode = "STRINGS"
	// CustomHivePartitioningMode allows custom definition of the external partitioning.
	CustomHivePartitioningMode HivePartitioningMode = "CUSTOM"
)

type HivePartitioningOptions added in v1.14.0 

type HivePartitioningOptions struct {

	// Mode defines which hive partitioning mode to use when reading data.
	Mode HivePartitioningMode

	// When hive partition detection is requested, a common prefix for
	// all source uris should be supplied.  The prefix must end immediately
	// before the partition key encoding begins.
	//
	// For example, consider files following this data layout.
	//   gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro
	//   gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro
	//
	// When hive partitioning is requested with either AUTO or STRINGS
	// detection, the common prefix can be either of
	// gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing
	// slash does not matter).
	SourceURIPrefix string

	// If set to true, queries against this external table require
	// a partition filter to be present that can perform partition
	// elimination.  Hive-partitioned load jobs with this field
	// set to true will fail.
	RequirePartitionFilter bool
}

HivePartitioningOptions defines the behavior of Hive partitioning when working with external data.

type IdentifierFormat added in v1.25.0 

type IdentifierFormat string

IdentifierFormat represents a how certain resource identifiers such as table references are formatted. 

var (
	// StandardSQLID returns an identifier suitable for use with Standard SQL.
	StandardSQLID IdentifierFormat = "SQL"

	// LegacySQLID returns an identifier suitable for use with Legacy SQL.
	LegacySQLID IdentifierFormat = "LEGACY_SQL"

	// StorageAPIResourceID returns an identifier suitable for use with the Storage API.  Namely, it's for formatting
	// a table resource for invoking read and write functionality.
	StorageAPIResourceID IdentifierFormat = "STORAGE_API_RESOURCE"

	// ErrUnknownIdentifierFormat is indicative of requesting an identifier in a format that is
	// not supported.
	ErrUnknownIdentifierFormat = errors.New("unknown identifier format")
)

type Inserter 

type Inserter struct {

	// SkipInvalidRows causes rows containing invalid data to be silently
	// ignored. The default value is false, which causes the entire request to
	// fail if there is an attempt to insert an invalid row.
	SkipInvalidRows bool

	// IgnoreUnknownValues causes values not matching the schema to be ignored.
	// The default value is false, which causes records containing such values
	// to be treated as invalid records.
	IgnoreUnknownValues bool

	// A TableTemplateSuffix allows Inserters to create tables automatically.
	//
	// Experimental: this option is experimental and may be modified or removed in future versions,
	// regardless of any other documented package stability guarantees. In general,
	// the BigQuery team recommends the use of partitioned tables over sharding
	// tables by suffix.
	//
	// When you specify a suffix, the table you upload data to
	// will be used as a template for creating a new table, with the same schema,
	// called <table> + <suffix>.
	//
	// More information is available at
	// https://cloud.google.com/bigquery/streaming-data-into-bigquery#template-tables
	TableTemplateSuffix string
	// contains filtered or unexported fields
}

An Inserter does streaming inserts into a BigQuery table. It is safe for concurrent use.

func (*Inserter) Put 

func (u *Inserter) Put(ctx context.Context, src interface{}) (err error)

Put uploads one or more rows to the BigQuery service.

If src is ValueSaver, then its Save method is called to produce a row for uploading.

If src is a struct or pointer to a struct, then a schema is inferred from it and used to create a StructSaver. The InsertID of the StructSaver will be empty.

If src is a slice of ValueSavers, structs, or struct pointers, then each element of the slice is treated as above, and multiple rows are uploaded.

Put returns a PutMultiError if one or more rows failed to be uploaded. The PutMultiError contains a RowInsertionError for each failed row.

Put will retry on temporary errors (see https://cloud.google.com/bigquery/troubleshooting-errors). This can result in duplicate rows if you do not use insert IDs. Also, if the error persists, the call will run indefinitely. Pass a context with a timeout to prevent hanging calls.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

type Item struct {
	Name  string
	Size  float64
	Count int
}

// Save implements the ValueSaver interface.
func (i *Item) Save() (map[string]bigquery.Value, string, error) {
	return map[string]bigquery.Value{
		"Name":  i.Name,
		"Size":  i.Size,
		"Count": i.Count,
	}, "", nil
}

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ins := client.Dataset("my_dataset").Table("my_table").Inserter()
	// Item implements the ValueSaver interface.
	items := []*Item{
		{Name: "n1", Size: 32.6, Count: 7},
		{Name: "n2", Size: 4, Count: 2},
		{Name: "n3", Size: 101.5, Count: 1},
	}
	if err := ins.Put(ctx, items); err != nil {
		// TODO: Handle error.
	}
}

Output:
Example (Struct) 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ins := client.Dataset("my_dataset").Table("my_table").Inserter()

	type score struct {
		Name string
		Num  int
	}
	scores := []score{
		{Name: "n1", Num: 12},
		{Name: "n2", Num: 31},
		{Name: "n3", Num: 7},
	}
	// Schema is inferred from the score type.
	if err := ins.Put(ctx, scores); err != nil {
		// TODO: Handle error.
	}
}

Output:
Example (StructSaver) 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

var schema bigquery.Schema

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ins := client.Dataset("my_dataset").Table("my_table").Inserter()

	type score struct {
		Name string
		Num  int
	}

	// Assume schema holds the table's schema.
	savers := []*bigquery.StructSaver{
		{Struct: score{Name: "n1", Num: 12}, Schema: schema, InsertID: "id1"},
		{Struct: score{Name: "n2", Num: 31}, Schema: schema, InsertID: "id2"},
		{Struct: score{Name: "n3", Num: 7}, Schema: schema, InsertID: "id3"},
	}
	if err := ins.Put(ctx, savers); err != nil {
		// TODO: Handle error.
	}
}

Output:
Example (ValuesSaver) 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

var schema bigquery.Schema

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}

	ins := client.Dataset("my_dataset").Table("my_table").Inserter()

	var vss []*bigquery.ValuesSaver
	for i, name := range []string{"n1", "n2", "n3"} {
		// Assume schema holds the table's schema.
		vss = append(vss, &bigquery.ValuesSaver{
			Schema:   schema,
			InsertID: name,
			Row:      []bigquery.Value{name, int64(i)},
		})
	}

	if err := ins.Put(ctx, vss); err != nil {
		// TODO: Handle error.
	}
}

Output:

type IntervalValue added in v1.32.0 

type IntervalValue struct {
	// In canonical form, Years and Months share a consistent sign and reduced
	// to avoid large month values.
	Years  int32
	Months int32

	// In canonical form, Days are independent of the other parts and can have it's
	// own sign.  There is no attempt to reduce larger Day values into the Y-M part.
	Days int32

	// In canonical form, the time parts all share a consistent sign and are reduced.
	Hours   int32
	Minutes int32
	Seconds int32
	// This represents the fractional seconds as nanoseconds.
	SubSecondNanos int32
}

IntervalValue is a go type for representing BigQuery INTERVAL values. Intervals are represented using three distinct parts: * Years and Months * Days * Time (Hours/Mins/Seconds/Fractional Seconds).

More information about BigQuery INTERVAL types can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#interval_type

IntervalValue is EXPERIMENTAL and subject to change or removal without notice.

func IntervalValueFromDuration added in v1.32.0 

func IntervalValueFromDuration(in time.Duration) *IntervalValue

IntervalValueFromDuration converts a time.Duration to an IntervalType representation.

The converted duration only leverages the hours/minutes/seconds part of the interval, the other parts representing days, months, and years are not used.

func ParseInterval added in v1.32.0 

func ParseInterval(value string) (*IntervalValue, error)

ParseInterval parses an interval in canonical string format and returns the IntervalValue it represents.

func (*IntervalValue) Canonicalize added in v1.32.0 

func (iv *IntervalValue) Canonicalize() *IntervalValue

Canonicalize returns an IntervalValue where signs for elements in the Y-M and H:M:S.F are consistent and values are normalized/reduced.

Canonical form enables more consistent comparison of the encoded interval. For example, encoding an interval with 12 months is equivalent to an interval of 1 year.

func (*IntervalValue) IsCanonical added in v1.32.0 

func (iv *IntervalValue) IsCanonical() bool

IsCanonical evaluates whether the current representation is in canonical form.

func (*IntervalValue) String added in v1.32.0 

func (iv *IntervalValue) String() string

String returns string representation of the interval value using the canonical format. The canonical format is as follows:

[sign]Y-M [sign]D [sign]H:M:S[.F]

func (*IntervalValue) ToDuration added in v1.32.0 

func (iv *IntervalValue) ToDuration() time.Duration

ToDuration converts an interval to a time.Duration value.

For the purposes of conversion: Years are normalized to 12 months. Months are normalized to 30 days. Days are normalized to 24 hours.

type Job 

type Job struct {
	// contains filtered or unexported fields
}

A Job represents an operation which has been submitted to BigQuery for processing.

func (*Job) Cancel 

func (j *Job) Cancel(ctx context.Context) error

Cancel requests that a job be cancelled. This method returns without waiting for cancellation to take effect. To check whether the job has terminated, use Job.Status. Cancelled jobs may still incur costs.

func (*Job) Children added in v1.2.0 

func (j *Job) Children(ctx context.Context) *JobIterator

Children returns a job iterator for enumerating child jobs of the current job. Currently only scripts, a form of query job, will create child jobs.

func (*Job) Config 

func (j *Job) Config() (JobConfig, error)

Config returns the configuration information for j.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ds := client.Dataset("my_dataset")
	job, err := ds.Table("t1").CopierFrom(ds.Table("t2")).Run(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	jc, err := job.Config()
	if err != nil {
		// TODO: Handle error.
	}
	copyConfig := jc.(*bigquery.CopyConfig)
	fmt.Println(copyConfig.Dst, copyConfig.CreateDisposition)
}

Output:

func (*Job) Delete added in v1.19.0 

func (j *Job) Delete(ctx context.Context) (err error)

Delete deletes the job.

func (*Job) Email 

func (j *Job) Email() string

Email returns the email of the job's creator.

func (*Job) ID 

func (j *Job) ID() string

ID returns the job's ID.

func (*Job) LastStatus 

func (j *Job) LastStatus() *JobStatus

LastStatus returns the most recently retrieved status of the job. The status is retrieved when a new job is created, or when JobFromID or Job.Status is called. Call Job.Status to get the most up-to-date information about a job.

func (*Job) Location 

func (j *Job) Location() string

Location returns the job's location.

func (*Job) ProjectID added in v1.19.0 

func (j *Job) ProjectID() string

ProjectID returns the job's associated project.

func (*Job) Read 

func (j *Job) Read(ctx context.Context) (ri *RowIterator, err error)

Read fetches the results of a query job. If j is not a query job, Read returns an error.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	q := client.Query("select name, num from t1")
	// Call Query.Run to get a Job, then call Read on the job.
	// Note: Query.Read is a shorthand for this.
	job, err := q.Run(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	it, err := job.Read(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	_ = it // TODO: iterate using Next or iterator.Pager.
}

Output:

func (*Job) Status 

func (j *Job) Status(ctx context.Context) (js *JobStatus, err error)

Status retrieves the current status of the job from BigQuery. It fails if the Status could not be determined.

func (*Job) Wait 

func (j *Job) Wait(ctx context.Context) (js *JobStatus, err error)

Wait blocks until the job or the context is done. It returns the final status of the job. If an error occurs while retrieving the status, Wait returns that error. But Wait returns nil if the status was retrieved successfully, even if status.Err() != nil. So callers must check both errors. See the example.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ds := client.Dataset("my_dataset")
	job, err := ds.Table("t1").CopierFrom(ds.Table("t2")).Run(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	status, err := job.Wait(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	if status.Err() != nil {
		// TODO: Handle error.
	}
}

Output:

type JobConfig 

type JobConfig interface {
	// contains filtered or unexported methods
}

JobConfig contains configuration information for a job. It is implemented by *CopyConfig, *ExtractConfig, *LoadConfig and *QueryConfig.

type JobIDConfig 

type JobIDConfig struct {
	// JobID is the ID to use for the job. If empty, a random job ID will be generated.
	JobID string

	// If AddJobIDSuffix is true, then a random string will be appended to JobID.
	AddJobIDSuffix bool

	// Location is the location for the job.
	Location string
}

JobIDConfig describes how to create an ID for a job.

type JobIterator 

type JobIterator struct {
	ProjectID       string    // Project ID of the jobs to list. Default is the client's project.
	AllUsers        bool      // Whether to list jobs owned by all users in the project, or just the current caller.
	State           State     // List only jobs in the given state. Defaults to all states.
	MinCreationTime time.Time // List only jobs created after this time.
	MaxCreationTime time.Time // List only jobs created before this time.
	ParentJobID     string    // List only jobs that are children of a given scripting job.
	// contains filtered or unexported fields
}

JobIterator iterates over jobs in a project.

func (*JobIterator) Next 

func (it *JobIterator) Next() (*Job, error)

Next returns the next Job. Its second return value is iterator.Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.

func (*JobIterator) PageInfo 

func (it *JobIterator) PageInfo() *iterator.PageInfo

PageInfo is a getter for the JobIterator's PageInfo.

type JobStatistics 

type JobStatistics struct {
	CreationTime        time.Time
	StartTime           time.Time
	EndTime             time.Time
	TotalBytesProcessed int64

	Details Statistics

	// NumChildJobs indicates the number of child jobs run as part of a script.
	NumChildJobs int64

	// ParentJobID indicates the origin job for jobs run as part of a script.
	ParentJobID string

	// ScriptStatistics includes information run as part of a child job within
	// a script.
	ScriptStatistics *ScriptStatistics

	// ReservationUsage attributes slot consumption to reservations.
	ReservationUsage []*ReservationUsage

	// TransactionInfo indicates the transaction ID associated with the job, if any.
	TransactionInfo *TransactionInfo

	// SessionInfo contains information about the session if this job is part of one.
	SessionInfo *SessionInfo
}

JobStatistics contains statistics about a job.

type JobStatus 

type JobStatus struct {
	State State

	// All errors encountered during the running of the job.
	// Not all Errors are fatal, so errors here do not necessarily mean that the job has completed or was unsuccessful.
	Errors []*Error

	// Statistics about the job.
	Statistics *JobStatistics
	// contains filtered or unexported fields
}

JobStatus contains the current State of a job, and errors encountered while processing that job.

func (*JobStatus) Done 

func (s *JobStatus) Done() bool

Done reports whether the job has completed. After Done returns true, the Err method will return an error if the job completed unsuccessfully.

func (*JobStatus) Err 

func (s *JobStatus) Err() error

Err returns the error that caused the job to complete unsuccessfully (if any).

type LoadConfig 

type LoadConfig struct {
	// Src is the source from which data will be loaded.
	Src LoadSource

	// Dst is the table into which the data will be loaded.
	Dst *Table

	// CreateDisposition specifies the circumstances under which the destination table will be created.
	// The default is CreateIfNeeded.
	CreateDisposition TableCreateDisposition

	// WriteDisposition specifies how existing data in the destination table is treated.
	// The default is WriteAppend.
	WriteDisposition TableWriteDisposition

	// The labels associated with this job.
	Labels map[string]string

	// If non-nil, the destination table is partitioned by time.
	TimePartitioning *TimePartitioning

	// If non-nil, the destination table is partitioned by integer range.
	RangePartitioning *RangePartitioning

	// Clustering specifies the data clustering configuration for the destination table.
	Clustering *Clustering

	// Custom encryption configuration (e.g., Cloud KMS keys).
	DestinationEncryptionConfig *EncryptionConfig

	// Allows the schema of the destination table to be updated as a side effect of
	// the load job.
	SchemaUpdateOptions []string

	// For Avro-based loads, controls whether logical type annotations are used.
	// See https://cloud.google.com/bigquery/docs/loading-data-cloud-storage-avro#logical_types
	// for additional information.
	UseAvroLogicalTypes bool

	// For ingestion from datastore backups, ProjectionFields governs which fields
	// are projected from the backup.  The default behavior projects all fields.
	ProjectionFields []string

	// HivePartitioningOptions allows use of Hive partitioning based on the
	// layout of objects in Cloud Storage.
	HivePartitioningOptions *HivePartitioningOptions

	// DecimalTargetTypes allows selection of how decimal values are converted when
	// processed in bigquery, subject to the value type having sufficient precision/scale
	// to support the values.  In the order of NUMERIC, BIGNUMERIC, and STRING, a type is
	// selected if is present in the list and if supports the necessary precision and scale.
	//
	// StringTargetType supports all precision and scale values.
	DecimalTargetTypes []DecimalTargetType

	// Sets a best-effort deadline on a specific job.  If job execution exceeds this
	// timeout, BigQuery may attempt to cancel this work automatically.
	//
	// This deadline cannot be adjusted or removed once the job is created.  Consider
	// using Job.Cancel in situations where you need more dynamic behavior.
	//
	// Experimental: this option is experimental and may be modified or removed in future versions,
	// regardless of any other documented package stability guarantees.
	JobTimeout time.Duration
}

LoadConfig holds the configuration for a load job.

type LoadSource 

type LoadSource interface {
	// contains filtered or unexported methods
}

A LoadSource represents a source of data that can be loaded into a BigQuery table.

This package defines two LoadSources: GCSReference, for Google Cloud Storage objects, and ReaderSource, for data read from an io.Reader.

type LoadStatistics 

type LoadStatistics struct {
	// The number of bytes of source data in a load job.
	InputFileBytes int64

	// The number of source files in a load job.
	InputFiles int64

	// Size of the loaded data in bytes. Note that while a load job is in the
	// running state, this value may change.
	OutputBytes int64

	// The number of rows imported in a load job. Note that while an import job is
	// in the running state, this value may change.
	OutputRows int64
}

LoadStatistics contains statistics about a load job.

type Loader 

type Loader struct {
	JobIDConfig
	LoadConfig
	// contains filtered or unexported fields
}

A Loader loads data from Google Cloud Storage into a BigQuery table.

func (*Loader) Run 

func (l *Loader) Run(ctx context.Context) (j *Job, err error)

Run initiates a load job.

type MaterializedViewDefinition added in v1.6.0 

type MaterializedViewDefinition struct {
	// EnableRefresh governs whether the derived view is updated to reflect
	// changes in the base table.
	EnableRefresh bool

	// LastRefreshTime reports the time, in millisecond precision, that the
	// materialized view was last updated.
	LastRefreshTime time.Time

	// Query contains the SQL query used to define the materialized view.
	Query string

	// RefreshInterval defines the maximum frequency, in millisecond precision,
	// at which this this materialized view will be refreshed.
	RefreshInterval time.Duration
}

MaterializedViewDefinition contains information for materialized views.

type Model 

type Model struct {
	ProjectID string
	DatasetID string
	// ModelID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_).
	// The maximum length is 1,024 characters.
	ModelID string
	// contains filtered or unexported fields
}

Model represent a reference to a BigQuery ML model. Within the API, models are used largely for communicating statistical information about a given model, as creation of models is only supported via BigQuery queries (e.g. CREATE MODEL .. AS ..).

For more info, see documentation for Bigquery ML, see: https://cloud.google.com/bigquery/docs/bigqueryml

func (*Model) Delete 

func (m *Model) Delete(ctx context.Context) (err error)

Delete deletes an ML model.

func (*Model) ExtractorTo added in v1.7.0 

func (m *Model) ExtractorTo(dst *GCSReference) *Extractor

ExtractorTo returns an Extractor which can be persist a BigQuery Model into Google Cloud Storage. The returned Extractor may be further configured before its Run method is called.

func (*Model) FullyQualifiedName 

func (m *Model) FullyQualifiedName() string

FullyQualifiedName returns the ID of the model in projectID:datasetID.modelid format.

func (*Model) Identifier added in v1.25.0 

func (m *Model) Identifier(f IdentifierFormat) (string, error)

Identifier returns the ID of the model in the requested format.

For Standard SQL format, the identifier will be quoted if the ProjectID contains dash (-) characters.

func (*Model) Metadata 

func (m *Model) Metadata(ctx context.Context) (mm *ModelMetadata, err error)

Metadata fetches the metadata for a model, which includes ML training statistics.

func (*Model) Update 

func (m *Model) Update(ctx context.Context, mm ModelMetadataToUpdate, etag string) (md *ModelMetadata, err error)

Update updates mutable fields in an ML model.

type ModelIterator 

type ModelIterator struct {
	// contains filtered or unexported fields
}

A ModelIterator is an iterator over Models.

func (*ModelIterator) Next 

func (it *ModelIterator) Next() (*Model, error)

Next returns the next result. Its second return value is Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.

func (*ModelIterator) PageInfo 

func (it *ModelIterator) PageInfo() *iterator.PageInfo

PageInfo supports pagination. See the google.golang.org/api/iterator package for details.

type ModelMetadata 

type ModelMetadata struct {
	// The user-friendly description of the model.
	Description string

	// The user-friendly name of the model.
	Name string

	// The type of the model.  Possible values include:
	// "LINEAR_REGRESSION" - a linear regression model
	// "LOGISTIC_REGRESSION" - a logistic regression model
	// "KMEANS" - a k-means clustering model
	Type string

	// The creation time of the model.
	CreationTime time.Time

	// The last modified time of the model.
	LastModifiedTime time.Time

	// The expiration time of the model.
	ExpirationTime time.Time

	// The geographic location where the model resides.  This value is
	// inherited from the encapsulating dataset.
	Location string

	// Custom encryption configuration (e.g., Cloud KMS keys).
	EncryptionConfig *EncryptionConfig

	Labels map[string]string

	// ETag is the ETag obtained when reading metadata. Pass it to Model.Update
	// to ensure that the metadata hasn't changed since it was read.
	ETag string
	// contains filtered or unexported fields
}

ModelMetadata represents information about a BigQuery ML model.

func (*ModelMetadata) RawFeatureColumns 

func (mm *ModelMetadata) RawFeatureColumns() ([]*StandardSQLField, error)

RawFeatureColumns exposes the underlying feature columns used to train an ML model and uses types from "google.golang.org/api/bigquery/v2", which are subject to change without warning. It is EXPERIMENTAL and subject to change or removal without notice.

func (*ModelMetadata) RawLabelColumns 

func (mm *ModelMetadata) RawLabelColumns() ([]*StandardSQLField, error)

RawLabelColumns exposes the underlying label columns used to train an ML model and uses types from "google.golang.org/api/bigquery/v2", which are subject to change without warning. It is EXPERIMENTAL and subject to change or removal without notice.

func (*ModelMetadata) RawTrainingRuns 

func (mm *ModelMetadata) RawTrainingRuns() []*TrainingRun

RawTrainingRuns exposes the underlying training run stats for a model using types from "google.golang.org/api/bigquery/v2", which are subject to change without warning. It is EXPERIMENTAL and subject to change or removal without notice.

type ModelMetadataToUpdate 

type ModelMetadataToUpdate struct {
	// The user-friendly description of this model.
	Description optional.String

	// The user-friendly name of this model.
	Name optional.String

	// The time when this model expires.  To remove a model's expiration,
	// set ExpirationTime to NeverExpire.  The zero value is ignored.
	ExpirationTime time.Time

	// The model's encryption configuration.
	EncryptionConfig *EncryptionConfig
	// contains filtered or unexported fields
}

ModelMetadataToUpdate is used when updating an ML model's metadata. Only non-nil fields will be updated.

func (*ModelMetadataToUpdate) DeleteLabel 

func (u *ModelMetadataToUpdate) DeleteLabel(name string)

DeleteLabel causes a label to be deleted on a call to Update.

func (*ModelMetadataToUpdate) SetLabel 

func (u *ModelMetadataToUpdate) SetLabel(name, value string)

SetLabel causes a label to be added or modified on a call to Update.

type MultiError 

type MultiError []error

A MultiError contains multiple related errors.

func (MultiError) Error 

func (m MultiError) Error() string

type NullBool 

type NullBool struct {
	Bool  bool
	Valid bool // Valid is true if Bool is not NULL.
}

NullBool represents a BigQuery BOOL that may be NULL.

func (NullBool) MarshalJSON 

func (n NullBool) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullBool to JSON.

func (NullBool) String 

func (n NullBool) String() string

func (*NullBool) UnmarshalJSON 

func (n *NullBool) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullBool.

type NullDate 

type NullDate struct {
	Date  civil.Date
	Valid bool // Valid is true if Date is not NULL.
}

NullDate represents a BigQuery DATE that may be null.

func (NullDate) MarshalJSON 

func (n NullDate) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullDate to JSON.

func (NullDate) String 

func (n NullDate) String() string

func (*NullDate) UnmarshalJSON 

func (n *NullDate) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullDate.

type NullDateTime 

type NullDateTime struct {
	DateTime civil.DateTime
	Valid    bool // Valid is true if DateTime is not NULL.
}

NullDateTime represents a BigQuery DATETIME that may be null.

func (NullDateTime) MarshalJSON 

func (n NullDateTime) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullDateTime to JSON.

func (NullDateTime) String 

func (n NullDateTime) String() string

func (*NullDateTime) UnmarshalJSON 

func (n *NullDateTime) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullDateTime.

type NullFloat64 

type NullFloat64 struct {
	Float64 float64
	Valid   bool // Valid is true if Float64 is not NULL.
}

NullFloat64 represents a BigQuery FLOAT64 that may be NULL.

func (NullFloat64) MarshalJSON 

func (n NullFloat64) MarshalJSON() (b []byte, err error)

MarshalJSON converts the NullFloat64 to JSON.

func (NullFloat64) String 

func (n NullFloat64) String() string

func (*NullFloat64) UnmarshalJSON 

func (n *NullFloat64) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullFloat64.

type NullGeography 

type NullGeography struct {
	GeographyVal string
	Valid        bool // Valid is true if GeographyVal is not NULL.
}

NullGeography represents a BigQuery GEOGRAPHY string that may be NULL.

func (NullGeography) MarshalJSON 

func (n NullGeography) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullGeography to JSON.

func (NullGeography) String 

func (n NullGeography) String() string

func (*NullGeography) UnmarshalJSON 

func (n *NullGeography) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullGeography.

type NullInt64 

type NullInt64 struct {
	Int64 int64
	Valid bool // Valid is true if Int64 is not NULL.
}

NullInt64 represents a BigQuery INT64 that may be NULL.

func (NullInt64) MarshalJSON 

func (n NullInt64) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullInt64 to JSON.

func (NullInt64) String 

func (n NullInt64) String() string

func (*NullInt64) UnmarshalJSON 

func (n *NullInt64) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullInt64.

type NullJSON added in v1.37.0 

type NullJSON struct {
	JSONVal string
	Valid   bool // Valid is true if JSONVal is not NULL.
}

NullJSON represents a BigQuery JSON string that may be NULL.

func (NullJSON) MarshalJSON added in v1.37.0 

func (n NullJSON) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullJSON to JSON.

func (NullJSON) String added in v1.37.0 

func (n NullJSON) String() string

func (*NullJSON) UnmarshalJSON added in v1.37.0 

func (n *NullJSON) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullJSON.

type NullString 

type NullString struct {
	StringVal string
	Valid     bool // Valid is true if StringVal is not NULL.
}

NullString represents a BigQuery STRING that may be NULL.

func (NullString) MarshalJSON 

func (n NullString) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullString to JSON.

func (NullString) String 

func (n NullString) String() string

func (*NullString) UnmarshalJSON 

func (n *NullString) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullString.

type NullTime 

type NullTime struct {
	Time  civil.Time
	Valid bool // Valid is true if Time is not NULL.
}

NullTime represents a BigQuery TIME that may be null.

func (NullTime) MarshalJSON 

func (n NullTime) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullTime to JSON.

func (NullTime) String 

func (n NullTime) String() string

func (*NullTime) UnmarshalJSON 

func (n *NullTime) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullTime.

type NullTimestamp 

type NullTimestamp struct {
	Timestamp time.Time
	Valid     bool // Valid is true if Time is not NULL.
}

NullTimestamp represents a BigQuery TIMESTAMP that may be null.

func (NullTimestamp) MarshalJSON 

func (n NullTimestamp) MarshalJSON() ([]byte, error)

MarshalJSON converts the NullTimestamp to JSON.

func (NullTimestamp) String 

func (n NullTimestamp) String() string

func (*NullTimestamp) UnmarshalJSON 

func (n *NullTimestamp) UnmarshalJSON(b []byte) error

UnmarshalJSON converts JSON into a NullTimestamp.

type ParquetOptions added in v1.18.0 

type ParquetOptions struct {
	// EnumAsString indicates whether to infer Parquet ENUM logical type as
	// STRING instead of BYTES by default.
	EnumAsString bool

	// EnableListInference indicates whether to use schema inference
	// specifically for Parquet LIST logical type.
	EnableListInference bool
}

ParquetOptions are additional options for Parquet external data sources.

type PolicyTagList added in v1.6.0 

type PolicyTagList struct {
	Names []string
}

PolicyTagList represents the annotations on a schema column for enforcing column-level security. For more information, see https://cloud.google.com/bigquery/docs/column-level-security-intro

type PutMultiError 

type PutMultiError []RowInsertionError

PutMultiError contains an error for each row which was not successfully inserted into a BigQuery table.

func (PutMultiError) Error 

func (pme PutMultiError) Error() string

type Query 

type Query struct {
	JobIDConfig
	QueryConfig
	// contains filtered or unexported fields
}

A Query queries data from a BigQuery table. Use Client.Query to create a Query.

func (*Query) Read 

func (q *Query) Read(ctx context.Context) (it *RowIterator, err error)

Read submits a query for execution and returns the results via a RowIterator. If the request can be satisfied by running using the optimized query path, it is used in place of the jobs.insert path as this path does not expose a job object.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	q := client.Query("select name, num from t1")
	it, err := q.Read(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	_ = it // TODO: iterate using Next or iterator.Pager.
}

Output:

func (*Query) Run 

func (q *Query) Run(ctx context.Context) (j *Job, err error)

Run initiates a query job.

type QueryConfig 

type QueryConfig struct {
	// Dst is the table into which the results of the query will be written.
	// If this field is nil, a temporary table will be created.
	Dst *Table

	// The query to execute. See https://cloud.google.com/bigquery/query-reference for details.
	Q string

	// DefaultProjectID and DefaultDatasetID specify the dataset to use for unqualified table names in the query.
	// If DefaultProjectID is set, DefaultDatasetID must also be set.
	DefaultProjectID string
	DefaultDatasetID string

	// TableDefinitions describes data sources outside of BigQuery.
	// The map keys may be used as table names in the query string.
	//
	// When a QueryConfig is returned from Job.Config, the map values
	// are always of type *ExternalDataConfig.
	TableDefinitions map[string]ExternalData

	// CreateDisposition specifies the circumstances under which the destination table will be created.
	// The default is CreateIfNeeded.
	CreateDisposition TableCreateDisposition

	// WriteDisposition specifies how existing data in the destination table is treated.
	// The default is WriteEmpty.
	WriteDisposition TableWriteDisposition

	// DisableQueryCache prevents results being fetched from the query cache.
	// If this field is false, results are fetched from the cache if they are available.
	// The query cache is a best-effort cache that is flushed whenever tables in the query are modified.
	// Cached results are only available when TableID is unspecified in the query's destination Table.
	// For more information, see https://cloud.google.com/bigquery/querying-data#querycaching
	DisableQueryCache bool

	// DisableFlattenedResults prevents results being flattened.
	// If this field is false, results from nested and repeated fields are flattened.
	// DisableFlattenedResults implies AllowLargeResults
	// For more information, see https://cloud.google.com/bigquery/docs/data#nested
	DisableFlattenedResults bool

	// AllowLargeResults allows the query to produce arbitrarily large result tables.
	// The destination must be a table.
	// When using this option, queries will take longer to execute, even if the result set is small.
	// For additional limitations, see https://cloud.google.com/bigquery/querying-data#largequeryresults
	AllowLargeResults bool

	// Priority specifies the priority with which to schedule the query.
	// The default priority is InteractivePriority.
	// For more information, see https://cloud.google.com/bigquery/querying-data#batchqueries
	Priority QueryPriority

	// MaxBillingTier sets the maximum billing tier for a Query.
	// Queries that have resource usage beyond this tier will fail (without
	// incurring a charge). If this field is zero, the project default will be used.
	MaxBillingTier int

	// MaxBytesBilled limits the number of bytes billed for
	// this job.  Queries that would exceed this limit will fail (without incurring
	// a charge).
	// If this field is less than 1, the project default will be
	// used.
	MaxBytesBilled int64

	// UseStandardSQL causes the query to use standard SQL. The default.
	// Deprecated: use UseLegacySQL.
	UseStandardSQL bool

	// UseLegacySQL causes the query to use legacy SQL.
	UseLegacySQL bool

	// Parameters is a list of query parameters. The presence of parameters
	// implies the use of standard SQL.
	// If the query uses positional syntax ("?"), then no parameter may have a name.
	// If the query uses named syntax ("@p"), then all parameters must have names.
	// It is illegal to mix positional and named syntax.
	Parameters []QueryParameter

	// TimePartitioning specifies time-based partitioning
	// for the destination table.
	TimePartitioning *TimePartitioning

	// RangePartitioning specifies integer range-based partitioning
	// for the destination table.
	RangePartitioning *RangePartitioning

	// Clustering specifies the data clustering configuration for the destination table.
	Clustering *Clustering

	// The labels associated with this job.
	Labels map[string]string

	// If true, don't actually run this job. A valid query will return a mostly
	// empty response with some processing statistics, while an invalid query will
	// return the same error it would if it wasn't a dry run.
	//
	// Query.Read will fail with dry-run queries. Call Query.Run instead, and then
	// call LastStatus on the returned job to get statistics. Calling Status on a
	// dry-run job will fail.
	DryRun bool

	// Custom encryption configuration (e.g., Cloud KMS keys).
	DestinationEncryptionConfig *EncryptionConfig

	// Allows the schema of the destination table to be updated as a side effect of
	// the query job.
	SchemaUpdateOptions []string

	// CreateSession will trigger creation of a new session when true.
	CreateSession bool

	// ConnectionProperties are optional key-values settings.
	ConnectionProperties []*ConnectionProperty

	// Sets a best-effort deadline on a specific job.  If job execution exceeds this
	// timeout, BigQuery may attempt to cancel this work automatically.
	//
	// This deadline cannot be adjusted or removed once the job is created.  Consider
	// using Job.Cancel in situations where you need more dynamic behavior.
	//
	// Experimental: this option is experimental and may be modified or removed in future versions,
	// regardless of any other documented package stability guarantees.
	JobTimeout time.Duration
}

QueryConfig holds the configuration for a query job.

type QueryParameter 

type QueryParameter struct {
	// Name is used for named parameter mode.
	// It must match the name in the query case-insensitively.
	Name string

	// Value is the value of the parameter.
	//
	// When you create a QueryParameter to send to BigQuery, the following Go types
	// are supported, with their corresponding Bigquery types:
	// int, int8, int16, int32, int64, uint8, uint16, uint32: INT64
	//   Note that uint, uint64 and uintptr are not supported, because
	//   they may contain values that cannot fit into a 64-bit signed integer.
	// float32, float64: FLOAT64
	// bool: BOOL
	// string: STRING
	// []byte: BYTES
	// time.Time: TIMESTAMP
	// *big.Rat: NUMERIC
	// *IntervalValue: INTERVAL
	// Arrays and slices of the above.
	// Structs of the above. Only the exported fields are used.
	//
	// For scalar values, you can supply the Null types within this library
	// to send the appropriate NULL values (e.g. NullInt64, NullString, etc).
	//
	// When a QueryParameter is returned inside a QueryConfig from a call to
	// Job.Config:
	// Integers are of type int64.
	// Floating-point values are of type float64.
	// Arrays are of type []interface{}, regardless of the array element type.
	// Structs are of type map[string]interface{}.
	//
	// When valid (non-null) Null types are sent, they come back as the Go types indicated
	// above.  Null strings will report in query statistics as a valid empty
	// string.
	Value interface{}
}

A QueryParameter is a parameter to a query.

type QueryPriority 

type QueryPriority string

QueryPriority specifies a priority with which a query is to be executed. 

const (
	// BatchPriority specifies that the query should be scheduled with the
	// batch priority.  BigQuery queues each batch query on your behalf, and
	// starts the query as soon as idle resources are available, usually within
	// a few minutes. If BigQuery hasn't started the query within 24 hours,
	// BigQuery changes the job priority to interactive. Batch queries don't
	// count towards your concurrent rate limit, which can make it easier to
	// start many queries at once.
	//
	// More information can be found at https://cloud.google.com/bigquery/docs/running-queries#batchqueries.
	BatchPriority QueryPriority = "BATCH"
	// InteractivePriority specifies that the query should be scheduled with
	// interactive priority, which means that the query is executed as soon as
	// possible. Interactive queries count towards your concurrent rate limit
	// and your daily limit. It is the default priority with which queries get
	// executed.
	//
	// More information can be found at https://cloud.google.com/bigquery/docs/running-queries#queries.
	InteractivePriority QueryPriority = "INTERACTIVE"
)

type QueryStatistics 

type QueryStatistics struct {

	// BI-Engine specific statistics.
	BIEngineStatistics *BIEngineStatistics

	// Billing tier for the job.
	BillingTier int64

	// Whether the query result was fetched from the query cache.
	CacheHit bool

	// The type of query statement, if valid.
	StatementType string

	// Total bytes billed for the job.
	TotalBytesBilled int64

	// Total bytes processed for the job.
	TotalBytesProcessed int64

	// For dry run queries, indicates how accurate the TotalBytesProcessed value is.
	// When indicated, values include:
	// UNKNOWN: accuracy of the estimate is unknown.
	// PRECISE: estimate is precise.
	// LOWER_BOUND: estimate is lower bound of what the query would cost.
	// UPPER_BOUND: estimate is upper bound of what the query would cost.
	TotalBytesProcessedAccuracy string

	// Describes execution plan for the query.
	QueryPlan []*ExplainQueryStage

	// The number of rows affected by a DML statement. Present only for DML
	// statements INSERT, UPDATE or DELETE.
	NumDMLAffectedRows int64

	// DMLStats provides statistics about the row mutations performed by
	// DML statements.
	DMLStats *DMLStatistics

	// Describes a timeline of job execution.
	Timeline []*QueryTimelineSample

	// ReferencedTables: [Output-only] Referenced tables for
	// the job. Queries that reference more than 50 tables will not have a
	// complete list.
	ReferencedTables []*Table

	// The schema of the results. Present only for successful dry run of
	// non-legacy SQL queries.
	Schema Schema

	// Slot-milliseconds consumed by this query job.
	SlotMillis int64

	// Standard SQL: list of undeclared query parameter names detected during a
	// dry run validation.
	UndeclaredQueryParameterNames []string

	// DDL target table.
	DDLTargetTable *Table

	// DDL Operation performed on the target table.  Used to report how the
	// query impacted the DDL target table.
	DDLOperationPerformed string

	// The DDL target table, present only for CREATE/DROP FUNCTION/PROCEDURE queries.
	DDLTargetRoutine *Routine
}

QueryStatistics contains statistics about a query job.

type QueryTimelineSample 

type QueryTimelineSample struct {

	// Total number of units currently being processed by workers, represented as largest value since last sample.
	ActiveUnits int64

	// Total parallel units of work completed by this query.
	CompletedUnits int64

	// Time elapsed since start of query execution.
	Elapsed time.Duration

	// Total parallel units of work remaining for the active stages.
	PendingUnits int64

	// Cumulative slot-milliseconds consumed by the query.
	SlotMillis int64
}

QueryTimelineSample represents a sample of execution statistics at a point in time.

type RangePartitioning added in v1.3.0 

type RangePartitioning struct {
	// The field by which the table is partitioned.
	// This field must be a top-level field, and must be typed as an
	// INTEGER/INT64.
	Field string
	// The details of how partitions are mapped onto the integer range.
	Range *RangePartitioningRange
}

RangePartitioning indicates an integer-range based storage organization strategy.

type RangePartitioningRange added in v1.3.0 

type RangePartitioningRange struct {
	// The start value of defined range of values, inclusive of the specified value.
	Start int64
	// The end of the defined range of values, exclusive of the defined value.
	End int64
	// The width of each interval range.
	Interval int64
}

RangePartitioningRange defines the boundaries and width of partitioned values.

type ReaderSource 

type ReaderSource struct {
	FileConfig
	// contains filtered or unexported fields
}

A ReaderSource is a source for a load operation that gets data from an io.Reader.

When a ReaderSource is part of a LoadConfig obtained via Job.Config, its internal io.Reader will be nil, so it cannot be used for a subsequent load operation.

func NewReaderSource 

func NewReaderSource(r io.Reader) *ReaderSource

NewReaderSource creates a ReaderSource from an io.Reader. You may optionally configure properties on the ReaderSource that describe the data being read, before passing it to Table.LoaderFrom.

type ReservationUsage added in v1.15.0 

type ReservationUsage struct {
	// SlotMillis reports the slot milliseconds utilized within in the given reservation.
	SlotMillis int64
	// Name indicates the utilized reservation name, or "unreserved" for ondemand usage.
	Name string
}

ReservationUsage contains information about a job's usage of a single reservation.

type Routine 

type Routine struct {
	ProjectID string
	DatasetID string
	RoutineID string
	// contains filtered or unexported fields
}

Routine represents a reference to a BigQuery routine. There are multiple types of routines including stored procedures and scalar user-defined functions (UDFs). For more information, see the BigQuery documentation at https://cloud.google.com/bigquery/docs/

func (*Routine) Create 

func (r *Routine) Create(ctx context.Context, rm *RoutineMetadata) (err error)

Create creates a Routine in the BigQuery service. Pass in a RoutineMetadata to define the routine.

func (*Routine) Delete 

func (r *Routine) Delete(ctx context.Context) (err error)

Delete removes a Routine from a dataset.

func (*Routine) FullyQualifiedName 

func (r *Routine) FullyQualifiedName() string

FullyQualifiedName returns an identifer for the routine in project.dataset.routine format.

func (*Routine) Identifier added in v1.25.0 

func (r *Routine) Identifier(f IdentifierFormat) (string, error)

Identifier returns the ID of the routine in the requested format.

For Standard SQL format, the identifier will be quoted if the ProjectID contains dash (-) characters.

func (*Routine) Metadata 

func (r *Routine) Metadata(ctx context.Context) (rm *RoutineMetadata, err error)

Metadata fetches the metadata for a given Routine.

func (*Routine) Update 

func (r *Routine) Update(ctx context.Context, upd *RoutineMetadataToUpdate, etag string) (rm *RoutineMetadata, err error)

Update modifies properties of a Routine using the API.

type RoutineArgument 

type RoutineArgument struct {
	// The name of this argument.  Can be absent for function return argument.
	Name string
	// Kind indicates the kind of argument represented.
	// Possible values:
	//   ARGUMENT_KIND_UNSPECIFIED
	//   FIXED_TYPE - The argument is a variable with fully specified
	//     type, which can be a struct or an array, but not a table.
	//   ANY_TYPE - The argument is any type, including struct or array,
	//     but not a table.
	Kind string
	// Mode is optional, and indicates whether an argument is input or output.
	// Mode can only be set for procedures.
	//
	// Possible values:
	//   MODE_UNSPECIFIED
	//   IN - The argument is input-only.
	//   OUT - The argument is output-only.
	//   INOUT - The argument is both an input and an output.
	Mode string
	// DataType provides typing information.  Unnecessary for ANY_TYPE Kind
	// arguments.
	DataType *StandardSQLDataType
}

RoutineArgument represents an argument supplied to a routine such as a UDF or stored procedured.

type RoutineDeterminism added in v1.15.0 

type RoutineDeterminism string

RoutineDeterminism specifies the level of determinism that javascript User Defined Functions exhibit. 

const (
	// Deterministic indicates that two calls with the same input to a UDF yield the same output.
	Deterministic RoutineDeterminism = "DETERMINISTIC"
	// NotDeterministic indicates that the output of the UDF is not guaranteed to yield the same
	// output each time for a given set of inputs.
	NotDeterministic RoutineDeterminism = "NOT_DETERMINISTIC"
)

type RoutineIterator 

type RoutineIterator struct {
	// contains filtered or unexported fields
}

A RoutineIterator is an iterator over Routines.

func (*RoutineIterator) Next 

func (it *RoutineIterator) Next() (*Routine, error)

Next returns the next result. Its second return value is Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.

func (*RoutineIterator) PageInfo 

func (it *RoutineIterator) PageInfo() *iterator.PageInfo

PageInfo supports pagination. See the google.golang.org/api/iterator package for details.

type RoutineMetadata 

type RoutineMetadata struct {
	ETag string
	// Type indicates the type of routine, such as SCALAR_FUNCTION, PROCEDURE,
	// or TABLE_VALUED_FUNCTION.
	Type         string
	CreationTime time.Time
	Description  string
	// DeterminismLevel is only applicable to Javascript UDFs.
	DeterminismLevel RoutineDeterminism
	LastModifiedTime time.Time
	// Language of the routine, such as SQL or JAVASCRIPT.
	Language string
	// The list of arguments for the the routine.
	Arguments  []*RoutineArgument
	ReturnType *StandardSQLDataType

	// Set only if the routine type is TABLE_VALUED_FUNCTION.
	ReturnTableType *StandardSQLTableType
	// For javascript routines, this indicates the paths for imported libraries.
	ImportedLibraries []string
	// Body contains the routine's body.
	// For functions, Body is the expression in the AS clause.
	//
	// For SQL functions, it is the substring inside the parentheses of a CREATE
	// FUNCTION statement.
	//
	// For JAVASCRIPT function, it is the evaluated string in the AS clause of
	// a CREATE FUNCTION statement.
	Body string
}

RoutineMetadata represents details of a given BigQuery Routine.

type RoutineMetadataToUpdate 

type RoutineMetadataToUpdate struct {
	Arguments         []*RoutineArgument
	Description       optional.String
	DeterminismLevel  optional.String
	Type              optional.String
	Language          optional.String
	Body              optional.String
	ImportedLibraries []string
	ReturnType        *StandardSQLDataType
	ReturnTableType   *StandardSQLTableType
}

RoutineMetadataToUpdate governs updating a routine.

type RowInsertionError 

type RowInsertionError struct {
	InsertID string // The InsertID associated with the affected row.
	RowIndex int    // The 0-based index of the affected row in the batch of rows being inserted.
	Errors   MultiError
}

RowInsertionError contains all errors that occurred when attempting to insert a row.

func (*RowInsertionError) Error 

func (e *RowInsertionError) Error() string

type RowIterator 

type RowIterator struct {

	// StartIndex can be set before the first call to Next. If PageInfo().Token
	// is also set, StartIndex is ignored.
	StartIndex uint64

	// The schema of the table. Available after the first call to Next.
	Schema Schema

	// The total number of rows in the result. Available after the first call to Next.
	// May be zero just after rows were inserted.
	TotalRows uint64
	// contains filtered or unexported fields
}

A RowIterator provides access to the result of a BigQuery lookup.

func (*RowIterator) Next 

func (it *RowIterator) Next(dst interface{}) error

Next loads the next row into dst. Its return value is iterator.Done if there are no more results. Once Next returns iterator.Done, all subsequent calls will return iterator.Done.

dst may implement ValueLoader, or may be a *[]Value, *map[string]Value, or struct pointer.

If dst is a *[]Value, it will be set to new []Value whose i'th element will be populated with the i'th column of the row.

If dst is a *map[string]Value, a new map will be created if dst is nil. Then for each schema column name, the map key of that name will be set to the column's value. STRUCT types (RECORD types or nested schemas) become nested maps.

If dst is pointer to a struct, each column in the schema will be matched with an exported field of the struct that has the same name, ignoring case. Unmatched schema columns and struct fields will be ignored.

Each BigQuery column type corresponds to one or more Go types; a matching struct field must be of the correct type. The correspondences are: 

STRING      string
BOOL        bool
INTEGER     int, int8, int16, int32, int64, uint8, uint16, uint32
FLOAT       float32, float64
BYTES       []byte
TIMESTAMP   time.Time
DATE        civil.Date
TIME        civil.Time
DATETIME    civil.DateTime

A repeated field corresponds to a slice or array of the element type. A STRUCT type (RECORD or nested schema) corresponds to a nested struct or struct pointer. All calls to Next on the same iterator must use the same struct type.

It is an error to attempt to read a BigQuery NULL value into a struct field, unless the field is of type []byte or is one of the special Null types: NullInt64, NullFloat64, NullBool, NullString, NullTimestamp, NullDate, NullTime or NullDateTime. You can also use a *[]Value or *map[string]Value to read from a table with NULLs.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
	"google.golang.org/api/iterator"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	q := client.Query("select name, num from t1")
	it, err := q.Read(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	for {
		var row []bigquery.Value
		err := it.Next(&row)
		if err == iterator.Done {
			break
		}
		if err != nil {
			// TODO: Handle error.
		}
		fmt.Println(row)
	}
}

Output:
Example (Struct) 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
	"google.golang.org/api/iterator"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}

	type score struct {
		Name string
		Num  int
	}

	q := client.Query("select name, num from t1")
	it, err := q.Read(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	for {
		var s score
		err := it.Next(&s)
		if err == iterator.Done {
			break
		}
		if err != nil {
			// TODO: Handle error.
		}
		fmt.Println(s)
	}
}

Output:

func (*RowIterator) PageInfo 

func (it *RowIterator) PageInfo() *iterator.PageInfo

PageInfo supports pagination. See the google.golang.org/api/iterator package for details.

func (*RowIterator) SourceJob added in v1.23.0 

func (ri *RowIterator) SourceJob() *Job

SourceJob returns an instance of a Job if the RowIterator is backed by a query, or a nil.

type Schema 

type Schema []*FieldSchema

Schema describes the fields in a table or query result.

func InferSchema 

func InferSchema(st interface{}) (Schema, error)

InferSchema tries to derive a BigQuery schema from the supplied struct value. Each exported struct field is mapped to a field in the schema.

The following BigQuery types are inferred from the corresponding Go types. (This is the same mapping as that used for RowIterator.Next.) Fields inferred from these types are marked required (non-nullable). 

STRING      string
BOOL        bool
INTEGER     int, int8, int16, int32, int64, uint8, uint16, uint32
FLOAT       float32, float64
BYTES       []byte
TIMESTAMP   time.Time
DATE        civil.Date
TIME        civil.Time
DATETIME    civil.DateTime
NUMERIC     *big.Rat

The big.Rat type supports numbers of arbitrary size and precision. Values will be rounded to 9 digits after the decimal point before being transmitted to BigQuery. See https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#numeric-type for more on NUMERIC.

A Go slice or array type is inferred to be a BigQuery repeated field of the element type. The element type must be one of the above listed types.

Due to lack of unique native Go type for GEOGRAPHY, there is no schema inference to GEOGRAPHY at this time.

Nullable fields are inferred from the NullXXX types, declared in this package: 

STRING      NullString
BOOL        NullBool
INTEGER     NullInt64
FLOAT       NullFloat64
TIMESTAMP   NullTimestamp
DATE        NullDate
TIME        NullTime
DATETIME    NullDateTime
GEOGRAPHY   NullGeography

For a nullable BYTES field, use the type []byte and tag the field "nullable" (see below). For a nullable NUMERIC field, use the type *big.Rat and tag the field "nullable".

A struct field that is of struct type is inferred to be a required field of type RECORD with a schema inferred recursively. For backwards compatibility, a field of type pointer to struct is also inferred to be required. To get a nullable RECORD field, use the "nullable" tag (see below).

InferSchema returns an error if any of the examined fields is of type uint, uint64, uintptr, map, interface, complex64, complex128, func, or chan. Future versions may handle these cases without error.

Recursively defined structs are also disallowed.

Struct fields may be tagged in a way similar to the encoding/json package. A tag of the form 

bigquery:"name"

uses "name" instead of the struct field name as the BigQuery field name. A tag of the form 

bigquery:"-"

omits the field from the inferred schema. The "nullable" option marks the field as nullable (not required). It is only needed for []byte, *big.Rat and pointer-to-struct fields, and cannot appear on other fields. In this example, the Go name of the field is retained: 

bigquery:",nullable"
Example 
package main

import (
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	type Item struct {
		Name  string
		Size  float64
		Count int
	}
	schema, err := bigquery.InferSchema(Item{})
	if err != nil {
		fmt.Println(err)
		// TODO: Handle error.
	}
	for _, fs := range schema {
		fmt.Println(fs.Name, fs.Type)
	}
}

Output:

Name STRING
Size FLOAT
Count INTEGER
Example (Tags) 
package main

import (
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	type Item struct {
		Name     string
		Size     float64
		Count    int    `bigquery:"number"`
		Secret   []byte `bigquery:"-"`
		Optional bigquery.NullBool
		OptBytes []byte `bigquery:",nullable"`
	}
	schema, err := bigquery.InferSchema(Item{})
	if err != nil {
		fmt.Println(err)
		// TODO: Handle error.
	}
	for _, fs := range schema {
		fmt.Println(fs.Name, fs.Type, fs.Required)
	}
}

Output:

Name STRING true
Size FLOAT true
number INTEGER true
Optional BOOLEAN false
OptBytes BYTES false

func SchemaFromJSON 

func SchemaFromJSON(schemaJSON []byte) (Schema, error)

SchemaFromJSON takes a native JSON BigQuery table schema definition and converts it to a populated Schema. The native API definition is used by tools such as the BQ CLI and https://github.com/GoogleCloudPlatform/protoc-gen-bq-schema.

The expected format is a JSON array of TableFieldSchema objects from the underlying API: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#TableFieldSchema

func (Schema) Relax added in v1.1.0 

func (s Schema) Relax() Schema

Relax returns a version of the schema where no fields are marked as Required.

func (Schema) ToJSONFields added in v1.31.0 

func (s Schema) ToJSONFields() ([]byte, error)

ToJSONFields exposes the schema as a JSON array of TableFieldSchema objects: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#TableFieldSchema

Generally this isn't needed for direct usage of this library, but is provided for use cases where you're interacting with other tools that consume the underlying API representation directly such as the BQ CLI tool.

type ScriptStackFrame added in v1.2.0 

type ScriptStackFrame struct {
	StartLine   int64
	StartColumn int64
	EndLine     int64
	EndColumn   int64
	// Name of the active procedure.  Empty if in a top-level script.
	ProcedureID string
	// Text of the current statement/expression.
	Text string
}

ScriptStackFrame represents the location of the statement/expression being evaluated.

Line and column numbers are defined as follows:

  • Line and column numbers start with one. That is, line 1 column 1 denotes the start of the script.
  • When inside a stored procedure, all line/column numbers are relative to the procedure body, not the script in which the procedure was defined.
  • Start/end positions exclude leading/trailing comments and whitespace. The end position always ends with a ";", when present.
  • Multi-byte Unicode characters are treated as just one column.
  • If the original script (or procedure definition) contains TAB characters, a tab "snaps" the indentation forward to the nearest multiple of 8 characters, plus 1. For example, a TAB on column 1, 2, 3, 4, 5, 6 , or 8 will advance the next character to column 9. A TAB on column 9, 10, 11, 12, 13, 14, 15, or 16 will advance the next character to column 17.

type ScriptStatistics added in v1.2.0 

type ScriptStatistics struct {
	EvaluationKind string
	StackFrames    []*ScriptStackFrame
}

ScriptStatistics report information about script-based query jobs.

type SessionInfo added in v1.23.0 

type SessionInfo struct {
	SessionID string
}

SessionInfo contains information about a session associated with a job.

type SnapshotDefinition added in v1.19.0 

type SnapshotDefinition struct {

	// BaseTableReference describes the ID of the table that this snapshot
	// came from.
	BaseTableReference *Table

	// SnapshotTime indicates when the base table was snapshot.
	SnapshotTime time.Time
}

SnapshotDefinition provides metadata related to the origin of a snapshot.

type StandardSQLDataType 

type StandardSQLDataType struct {
	// ArrayElementType indicates the type of an array's elements, when the
	// TypeKind is ARRAY.
	ArrayElementType *StandardSQLDataType
	// StructType indicates the struct definition (fields), when the
	// TypeKind is STRUCT.
	StructType *StandardSQLStructType
	// The top-level type of this type definition.
	// Can be any standard SQL data type.  For more information about BigQuery
	// data types, see
	// https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types
	//
	// Additional information is available in the REST documentation:
	// https://cloud.google.com/bigquery/docs/reference/rest/v2/StandardSqlDataType
	TypeKind string
}

StandardSQLDataType conveys type information using the Standard SQL type system.

type StandardSQLField 

type StandardSQLField struct {
	// The name of this field.  Can be absent for struct fields.
	Name string
	// Data type for the field.
	Type *StandardSQLDataType
}

StandardSQLField represents a field using the Standard SQL data type system.

type StandardSQLStructType 

type StandardSQLStructType struct {
	Fields []*StandardSQLField
}

StandardSQLStructType represents a structure type, which is a list of Standard SQL fields. For more information, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#struct-type

type StandardSQLTableType added in v1.19.0 

type StandardSQLTableType struct {

	// The columns of the table.
	Columns []*StandardSQLField
}

StandardSQLTableType models a table-like resource, which has a set of columns.

type State 

type State int

State is one of a sequence of states that a Job progresses through as it is processed. 

const (
	// StateUnspecified is the default JobIterator state.
	StateUnspecified State = iota
	// Pending is a state that describes that the job is pending.
	Pending
	// Running is a state that describes that the job is running.
	Running
	// Done is a state that describes that the job is done.
	Done
)

type Statistics 

type Statistics interface {
	// contains filtered or unexported methods
}

Statistics is one of ExtractStatistics, LoadStatistics or QueryStatistics.

type StreamingBuffer 

type StreamingBuffer struct {
	// A lower-bound estimate of the number of bytes currently in the streaming
	// buffer.
	EstimatedBytes uint64

	// A lower-bound estimate of the number of rows currently in the streaming
	// buffer.
	EstimatedRows uint64

	// The time of the oldest entry in the streaming buffer.
	OldestEntryTime time.Time
}

StreamingBuffer holds information about the streaming buffer.

type StructSaver 

type StructSaver struct {
	// Schema determines what fields of the struct are uploaded. It should
	// match the table's schema.
	// Schema is optional for StructSavers that are passed to Uploader.Put.
	Schema Schema

	// InsertID governs the best-effort deduplication feature of
	// BigQuery streaming inserts.
	//
	// If the InsertID is empty, a random InsertID will be generated by
	// this library to facilitate deduplication.
	//
	// If the InsertID is set to the sentinel value NoDedupeID, an InsertID
	// is not sent.
	//
	// For all other non-empty values, BigQuery will use the provided
	// value for best-effort deduplication.
	InsertID string

	// Struct should be a struct or a pointer to a struct.
	Struct interface{}
}

StructSaver implements ValueSaver for a struct. The struct is converted to a map of values by using the values of struct fields corresponding to schema fields. Additional and missing fields are ignored, as are nested struct pointers that are nil.

func (*StructSaver) Save 

func (ss *StructSaver) Save() (row map[string]Value, insertID string, err error)

Save implements ValueSaver.

type Table 

type Table struct {
	// ProjectID, DatasetID and TableID may be omitted if the Table is the destination for a query.
	// In this case the result will be stored in an ephemeral table.
	ProjectID string
	DatasetID string
	// TableID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_).
	// The maximum length is 1,024 characters.
	TableID string
	// contains filtered or unexported fields
}

A Table is a reference to a BigQuery table.

func (*Table) CopierFrom 

func (t *Table) CopierFrom(srcs ...*Table) *Copier

CopierFrom returns a Copier which can be used to copy data into a BigQuery table from one or more BigQuery tables. The returned Copier may optionally be further configured before its Run method is called.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ds := client.Dataset("my_dataset")
	c := ds.Table("combined").CopierFrom(ds.Table("t1"), ds.Table("t2"))
	c.WriteDisposition = bigquery.WriteTruncate
	// TODO: set other options on the Copier.
	job, err := c.Run(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	status, err := job.Wait(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	if status.Err() != nil {
		// TODO: Handle error.
	}
}

Output:

func (*Table) Create 

func (t *Table) Create(ctx context.Context, tm *TableMetadata) (err error)

Create creates a table in the BigQuery service. Pass in a TableMetadata value to configure the table. If tm.View.Query is non-empty, the created table will be of type VIEW. If no ExpirationTime is specified, the table will never expire. After table creation, a view can be modified only if its table was initially created with a view.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	t := client.Dataset("my_dataset").Table("new-table")
	if err := t.Create(ctx, nil); err != nil {
		// TODO: Handle error.
	}
}

Output:
Example (EncryptionKey)

This example demonstrates how to create a table with a customer-managed encryption key. 

package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	// Infer table schema from a Go type.
	schema, err := bigquery.InferSchema(Item{})
	if err != nil {
		// TODO: Handle error.
	}
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	t := client.Dataset("my_dataset").Table("new-table")

	// TODO: Replace this key with a key you have created in Cloud KMS.
	keyName := "projects/P/locations/L/keyRings/R/cryptoKeys/K"
	if err := t.Create(ctx,
		&bigquery.TableMetadata{
			Name:             "My New Table",
			Schema:           schema,
			EncryptionConfig: &bigquery.EncryptionConfig{KMSKeyName: keyName},
		}); err != nil {
		// TODO: Handle error.
	}
}

type Item struct {
	Name  string
	Size  float64
	Count int
}

// Save implements the ValueSaver interface.
func (i *Item) Save() (map[string]bigquery.Value, string, error) {
	return map[string]bigquery.Value{
		"Name":  i.Name,
		"Size":  i.Size,
		"Count": i.Count,
	}, "", nil
}

Output:
Example (Initialize)

Initialize a new table by passing TableMetadata to Table.Create. 

package main

import (
	"context"
	"time"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	// Infer table schema from a Go type.
	schema, err := bigquery.InferSchema(Item{})
	if err != nil {
		// TODO: Handle error.
	}
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	t := client.Dataset("my_dataset").Table("new-table")
	if err := t.Create(ctx,
		&bigquery.TableMetadata{
			Name:           "My New Table",
			Schema:         schema,
			ExpirationTime: time.Now().Add(24 * time.Hour),
		}); err != nil {
		// TODO: Handle error.
	}
}

type Item struct {
	Name  string
	Size  float64
	Count int
}

// Save implements the ValueSaver interface.
func (i *Item) Save() (map[string]bigquery.Value, string, error) {
	return map[string]bigquery.Value{
		"Name":  i.Name,
		"Size":  i.Size,
		"Count": i.Count,
	}, "", nil
}

Output:

func (*Table) Delete 

func (t *Table) Delete(ctx context.Context) (err error)

Delete deletes the table.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	if err := client.Dataset("my_dataset").Table("my_table").Delete(ctx); err != nil {
		// TODO: Handle error.
	}
}

Output:

func (*Table) ExtractorTo 

func (t *Table) ExtractorTo(dst *GCSReference) *Extractor

ExtractorTo returns an Extractor which can be used to extract data from a BigQuery table into Google Cloud Storage. The returned Extractor may optionally be further configured before its Run method is called.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	gcsRef := bigquery.NewGCSReference("gs://my-bucket/my-object")
	gcsRef.FieldDelimiter = ":"
	// TODO: set other options on the GCSReference.
	ds := client.Dataset("my_dataset")
	extractor := ds.Table("my_table").ExtractorTo(gcsRef)
	extractor.DisableHeader = true
	// TODO: set other options on the Extractor.
	job, err := extractor.Run(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	status, err := job.Wait(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	if status.Err() != nil {
		// TODO: Handle error.
	}
}

Output:

func (*Table) FullyQualifiedName 

func (t *Table) FullyQualifiedName() string

FullyQualifiedName returns the ID of the table in projectID:datasetID.tableID format.

func (*Table) IAM added in v1.9.0 

func (t *Table) IAM() *iam.Handle

IAM provides access to an iam.Handle that allows access to IAM functionality for the given BigQuery table. For more information, see https://pkg.go.dev/cloud.google.com/go/iam

func (*Table) Identifier added in v1.25.0 

func (t *Table) Identifier(f IdentifierFormat) (string, error)

Identifier returns the ID of the table in the requested format.

func (*Table) Inserter 

func (t *Table) Inserter() *Inserter

Inserter returns an Inserter that can be used to append rows to t. The returned Inserter may optionally be further configured before its Put method is called.

To stream rows into a date-partitioned table at a particular date, add the $yyyymmdd suffix to the table name when constructing the Table.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ins := client.Dataset("my_dataset").Table("my_table").Inserter()
	_ = ins // TODO: Use ins.
}

Output:
Example (Options) 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	ins := client.Dataset("my_dataset").Table("my_table").Inserter()
	ins.SkipInvalidRows = true
	ins.IgnoreUnknownValues = true
	_ = ins // TODO: Use ins.
}

Output:

func (*Table) LoaderFrom 

func (t *Table) LoaderFrom(src LoadSource) *Loader

LoaderFrom returns a Loader which can be used to load data into a BigQuery table. The returned Loader may optionally be further configured before its Run method is called. See GCSReference and ReaderSource for additional configuration options that affect loading.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	gcsRef := bigquery.NewGCSReference("gs://my-bucket/my-object")
	gcsRef.AllowJaggedRows = true
	gcsRef.MaxBadRecords = 5
	gcsRef.Schema = schema
	// TODO: set other options on the GCSReference.
	ds := client.Dataset("my_dataset")
	loader := ds.Table("my_table").LoaderFrom(gcsRef)
	loader.CreateDisposition = bigquery.CreateNever
	// TODO: set other options on the Loader.
	job, err := loader.Run(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	status, err := job.Wait(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	if status.Err() != nil {
		// TODO: Handle error.
	}
}

var schema bigquery.Schema

Output:
Example (Reader) 
package main

import (
	"context"
	"os"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	f, err := os.Open("data.csv")
	if err != nil {
		// TODO: Handle error.
	}
	rs := bigquery.NewReaderSource(f)
	rs.AllowJaggedRows = true
	rs.MaxBadRecords = 5
	rs.Schema = schema
	// TODO: set other options on the GCSReference.
	ds := client.Dataset("my_dataset")
	loader := ds.Table("my_table").LoaderFrom(rs)
	loader.CreateDisposition = bigquery.CreateNever
	// TODO: set other options on the Loader.
	job, err := loader.Run(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	status, err := job.Wait(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	if status.Err() != nil {
		// TODO: Handle error.
	}
}

var schema bigquery.Schema

Output:

func (*Table) Metadata 

func (t *Table) Metadata(ctx context.Context, opts ...TableMetadataOption) (md *TableMetadata, err error)

Metadata fetches the metadata for the table.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	md, err := client.Dataset("my_dataset").Table("my_table").Metadata(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(md)
}

Output:

func (*Table) Read 

func (t *Table) Read(ctx context.Context) *RowIterator

Read fetches the contents of the table.

Example 
package main

import (
	"context"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	it := client.Dataset("my_dataset").Table("my_table").Read(ctx)
	_ = it // TODO: iterate using Next or iterator.Pager.
}

Output:

func (*Table) Update 

func (t *Table) Update(ctx context.Context, tm TableMetadataToUpdate, etag string, opts ...TableUpdateOption) (md *TableMetadata, err error)

Update modifies specific Table metadata fields.

Example (BlindWrite)

To perform a blind write, ignoring the existing state (and possibly overwriting other updates), pass the empty string as the etag. 

package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	t := client.Dataset("my_dataset").Table("my_table")
	tm, err := t.Update(ctx, bigquery.TableMetadataToUpdate{
		Description: "my favorite table",
	}, "")
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(tm)
}

Output:
Example (ReadModifyWrite)

This example illustrates how to perform a read-modify-write sequence on table metadata. Passing the metadata's ETag to the Update call ensures that the call will fail if the metadata was changed since the read. 

package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	t := client.Dataset("my_dataset").Table("my_table")
	md, err := t.Metadata(ctx)
	if err != nil {
		// TODO: Handle error.
	}
	md2, err := t.Update(ctx,
		bigquery.TableMetadataToUpdate{Name: "new " + md.Name},
		md.ETag)
	if err != nil {
		// TODO: Handle error.
	}
	fmt.Println(md2)
}

Output:

func (*Table) Uploader 

func (t *Table) Uploader() *Inserter

Uploader calls Inserter. Deprecated: use Table.Inserter instead.

type TableCopyOperationType added in v1.19.0 

type TableCopyOperationType string

TableCopyOperationType is used to indicate the type of operation performed by a BigQuery copy job. 

var (
	// CopyOperation indicates normal table to table copying.
	CopyOperation TableCopyOperationType = "COPY"
	// SnapshotOperation indicates creating a snapshot from a regular table, which
	// operates as an immutable copy.
	SnapshotOperation TableCopyOperationType = "SNAPSHOT"
	// RestoreOperation indicates creating/restoring a table from a snapshot.
	RestoreOperation TableCopyOperationType = "RESTORE"
	// CloneOperation indicates creating a table clone, which creates a writeable
	// copy of a base table that is billed based on difference from the base table.
	CloneOperation TableCopyOperationType = "CLONE"
)

type TableCreateDisposition 

type TableCreateDisposition string

TableCreateDisposition specifies the circumstances under which destination table will be created. Default is CreateIfNeeded. 

const (
	// CreateIfNeeded will create the table if it does not already exist.
	// Tables are created atomically on successful completion of a job.
	CreateIfNeeded TableCreateDisposition = "CREATE_IF_NEEDED"

	// CreateNever ensures the table must already exist and will not be
	// automatically created.
	CreateNever TableCreateDisposition = "CREATE_NEVER"
)

type TableIterator 

type TableIterator struct {
	// contains filtered or unexported fields
}

A TableIterator is an iterator over Tables.

func (*TableIterator) Next 

func (it *TableIterator) Next() (*Table, error)

Next returns the next result. Its second return value is Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.

Example 
package main

import (
	"context"
	"fmt"

	"cloud.google.com/go/bigquery"
	"google.golang.org/api/iterator"
)

func main() {
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, "project-id")
	if err != nil {
		// TODO: Handle error.
	}
	it := client.Dataset("my_dataset").Tables(ctx)
	for {
		t, err := it.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			// TODO: Handle error.
		}
		fmt.Println(t)
	}
}

Output:

func (*TableIterator) PageInfo 

func (it *TableIterator) PageInfo() *iterator.PageInfo

PageInfo supports pagination. See the google.golang.org/api/iterator package for details.

type TableMetadata 

type TableMetadata struct {

	// The user-friendly name for the table.
	Name string

	// Output-only location of the table, based on the encapsulating dataset.
	Location string

	// The user-friendly description of the table.
	Description string

	// The table schema. If provided on create, ViewQuery must be empty.
	Schema Schema

	// If non-nil, this table is a materialized view.
	MaterializedView *MaterializedViewDefinition

	// The query to use for a logical view. If provided on create, Schema must be nil.
	ViewQuery string

	// Use Legacy SQL for the view query.
	// At most one of UseLegacySQL and UseStandardSQL can be true.
	UseLegacySQL bool

	// Use Standard SQL for the view query. The default.
	// At most one of UseLegacySQL and UseStandardSQL can be true.
	// Deprecated: use UseLegacySQL.
	UseStandardSQL bool

	// If non-nil, the table is partitioned by time. Only one of
	// time partitioning or range partitioning can be specified.
	TimePartitioning *TimePartitioning

	// If non-nil, the table is partitioned by integer range.  Only one of
	// time partitioning or range partitioning can be specified.
	RangePartitioning *RangePartitioning

	// If set to true, queries that reference this table must specify a
	// partition filter (e.g. a WHERE clause) that can be used to eliminate
	// partitions. Used to prevent unintentional full data scans on large
	// partitioned tables.
	RequirePartitionFilter bool

	// Clustering specifies the data clustering configuration for the table.
	Clustering *Clustering

	// The time when this table expires. If set, this table will expire at the
	// specified time. Expired tables will be deleted and their storage
	// reclaimed. The zero value is ignored.
	ExpirationTime time.Time

	// User-provided labels.
	Labels map[string]string

	// Information about a table stored outside of BigQuery.
	ExternalDataConfig *ExternalDataConfig

	// Custom encryption configuration (e.g., Cloud KMS keys).
	EncryptionConfig *EncryptionConfig

	FullID           string // An opaque ID uniquely identifying the table.
	Type             TableType
	CreationTime     time.Time
	LastModifiedTime time.Time

	// The size of the table in bytes.
	// This does not include data that is being buffered during a streaming insert.
	NumBytes int64

	// The number of bytes in the table considered "long-term storage" for reduced
	// billing purposes.  See https://cloud.google.com/bigquery/pricing#long-term-storage
	// for more information.
	NumLongTermBytes int64

	// The number of rows of data in this table.
	// This does not include data that is being buffered during a streaming insert.
	NumRows uint64

	// SnapshotDefinition contains additional information about the provenance of a
	// given snapshot table.
	SnapshotDefinition *SnapshotDefinition

	// CloneDefinition contains additional information about the provenance of a
	// given cloned table.
	CloneDefinition *CloneDefinition

	// Contains information regarding this table's streaming buffer, if one is
	// present. This field will be nil if the table is not being streamed to or if
	// there is no data in the streaming buffer.
	StreamingBuffer *StreamingBuffer

	// ETag is the ETag obtained when reading metadata. Pass it to Table.Update to
	// ensure that the metadata hasn't changed since it was read.
	ETag string
}

TableMetadata contains information about a BigQuery table.

type TableMetadataOption added in v1.33.0 

type TableMetadataOption func(*tableGetCall)

TableMetadataOption allow requests to alter requests for table metadata.

func WithMetadataView added in v1.33.0 

func WithMetadataView(tmv TableMetadataView) TableMetadataOption

WithMetadataView is used to customize what details are returned when interrogating a table via the Metadata() call. Generally this is used to limit data returned for performance reasons (such as large tables that take time computing storage statistics).

type TableMetadataToUpdate 

type TableMetadataToUpdate struct {
	// The user-friendly description of this table.
	Description optional.String

	// The user-friendly name for this table.
	Name optional.String

	// The table's schema.
	// When updating a schema, you can add columns but not remove them.
	Schema Schema

	// The table's clustering configuration.
	// For more information on how modifying clustering affects the table, see:
	// https://cloud.google.com/bigquery/docs/creating-clustered-tables#modifying-cluster-spec
	Clustering *Clustering

	// The table's encryption configuration.
	EncryptionConfig *EncryptionConfig

	// The time when this table expires. To remove a table's expiration,
	// set ExpirationTime to NeverExpire. The zero value is ignored.
	ExpirationTime time.Time

	// ExternalDataConfig controls the definition of a table defined against
	// an external source, such as one based on files in Google Cloud Storage.
	ExternalDataConfig *ExternalDataConfig

	// The query to use for a view.
	ViewQuery optional.String

	// Use Legacy SQL for the view query.
	UseLegacySQL optional.Bool

	// MaterializedView allows changes to the underlying materialized view
	// definition. When calling Update, ensure that all mutable fields of
	// MaterializedViewDefinition are populated.
	MaterializedView *MaterializedViewDefinition

	// TimePartitioning allows modification of certain aspects of partition
	// configuration such as partition expiration and whether partition
	// filtration is required at query time.  When calling Update, ensure
	// that all mutable fields of TimePartitioning are populated.
	TimePartitioning *TimePartitioning

	// RequirePartitionFilter governs whether the table enforces partition
	// elimination when referenced in a query.
	RequirePartitionFilter optional.Bool
	// contains filtered or unexported fields
}

TableMetadataToUpdate is used when updating a table's metadata. Only non-nil fields will be updated.

func (*TableMetadataToUpdate) DeleteLabel 

func (u *TableMetadataToUpdate) DeleteLabel(name string)

DeleteLabel causes a label to be deleted on a call to Update.

func (*TableMetadataToUpdate) SetLabel 

func (u *TableMetadataToUpdate) SetLabel(name, value string)

SetLabel causes a label to be added or modified on a call to Update.

type TableMetadataView added in v1.33.0 

type TableMetadataView string

TableMetadataView specifies which details about a table are desired. 

const (
	// BasicMetadataView populates basic table information including schema partitioning,
	// but does not contain storage statistics like number or rows or bytes.  This is a more
	// efficient view to use for large tables or higher metadata query rates.
	BasicMetadataView TableMetadataView = "BASIC"

	// FullMetadataView returns all table information, including storage statistics.  It currently
	// returns the same information as StorageStatsMetadataView, but may include additional information
	// in the future.
	FullMetadataView TableMetadataView = "FULL"

	// StorageStatsMetadataView includes all information from the basic view, and includes storage statistics.  It currently
	StorageStatsMetadataView TableMetadataView = "STORAGE_STATS"
)

type TableType 

type TableType string

TableType is the type of table. 

const (
	// RegularTable is a regular table.
	RegularTable TableType = "TABLE"
	// ViewTable is a table type describing that the table is a logical view.
	// See more information at https://cloud.google.com/bigquery/docs/views.
	ViewTable TableType = "VIEW"
	// ExternalTable is a table type describing that the table is an external
	// table (also known as a federated data source). See more information at
	// https://cloud.google.com/bigquery/external-data-sources.
	ExternalTable TableType = "EXTERNAL"
	// MaterializedView represents a managed storage table that's derived from
	// a base table.
	MaterializedView TableType = "MATERIALIZED_VIEW"
	// Snapshot represents an immutable point in time snapshot of some other
	// table.
	Snapshot TableType = "SNAPSHOT"
)

type TableUpdateOption added in v1.32.0 

type TableUpdateOption func(*tablePatchCall)

TableUpdateOption allow requests to update table metadata.

func WithAutoDetectSchema added in v1.32.0 

func WithAutoDetectSchema(b bool) TableUpdateOption

WithAutoDetectSchema governs whether the schema autodetection occurs as part of the table update. This is relevant in cases like external tables where schema is detected from the source data.

type TableWriteDisposition 

type TableWriteDisposition string

TableWriteDisposition specifies how existing data in a destination table is treated. Default is WriteAppend. 

const (
	// WriteAppend will append to any existing data in the destination table.
	// Data is appended atomically on successful completion of a job.
	WriteAppend TableWriteDisposition = "WRITE_APPEND"

	// WriteTruncate overrides the existing data in the destination table.
	// Data is overwritten atomically on successful completion of a job.
	WriteTruncate TableWriteDisposition = "WRITE_TRUNCATE"

	// WriteEmpty fails writes if the destination table already contains data.
	WriteEmpty TableWriteDisposition = "WRITE_EMPTY"
)

type TimePartitioning 

type TimePartitioning struct {
	// Defines the partition interval type.  Supported values are "HOUR", "DAY", "MONTH", and "YEAR".
	// When the interval type is not specified, default behavior is DAY.
	Type TimePartitioningType

	// The amount of time to keep the storage for a partition.
	// If the duration is empty (0), the data in the partitions do not expire.
	Expiration time.Duration

	// If empty, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the
	// table is partitioned by this field. The field must be a top-level TIMESTAMP or
	// DATE field. Its mode must be NULLABLE or REQUIRED.
	Field string

	// If set to true, queries that reference this table must specify a
	// partition filter (e.g. a WHERE clause) that can be used to eliminate
	// partitions. Used to prevent unintentional full data scans on large
	// partitioned tables.
	// DEPRECATED: use the top-level RequirePartitionFilter in TableMetadata.
	RequirePartitionFilter bool
}

TimePartitioning describes the time-based date partitioning on a table. For more information see: https://cloud.google.com/bigquery/docs/creating-partitioned-tables.

type TimePartitioningType added in v1.8.0 

type TimePartitioningType string

TimePartitioningType defines the interval used to partition managed data. 

const (
	// DayPartitioningType uses a day-based interval for time partitioning.
	DayPartitioningType TimePartitioningType = "DAY"

	// HourPartitioningType uses an hour-based interval for time partitioning.
	HourPartitioningType TimePartitioningType = "HOUR"

	// MonthPartitioningType uses a month-based interval for time partitioning.
	MonthPartitioningType TimePartitioningType = "MONTH"

	// YearPartitioningType uses a year-based interval for time partitioning.
	YearPartitioningType TimePartitioningType = "YEAR"
)

type TrainingRun 

type TrainingRun bq.TrainingRun

TrainingRun represents information about a single training run for a BigQuery ML model. Experimental: This information may be modified or removed in future versions of this package.

type TransactionInfo added in v1.20.1 

type TransactionInfo struct {
	// TransactionID is the system-generated identifier for the transaction.
	TransactionID string
}

TransactionInfo contains information about a multi-statement transaction that may have associated with a job.

type Uploader 

type Uploader = Inserter

Uploader is an obsolete name for Inserter.

type Value 

type Value interface{}

Value stores the contents of a single cell from a BigQuery result.

type ValueLoader 

type ValueLoader interface {
	Load(v []Value, s Schema) error
}

ValueLoader stores a slice of Values representing a result row from a Read operation. See RowIterator.Next for more information.

type ValueSaver 

type ValueSaver interface {
	// Save returns a row to be inserted into a BigQuery table, represented
	// as a map from field name to Value.
	// The insertID governs the best-effort deduplication feature of
	// BigQuery streaming inserts.
	//
	// If the insertID is empty, a random insertID will be generated by
	// this library to facilitate deduplication.
	//
	// If the insertID is set to the sentinel value NoDedupeID, an insertID
	// is not sent.
	//
	// For all other non-empty values, BigQuery will use the provided
	// value for best-effort deduplication.
	Save() (row map[string]Value, insertID string, err error)
}

A ValueSaver returns a row of data to be inserted into a table.

type ValuesSaver 

type ValuesSaver struct {
	Schema Schema

	// InsertID governs the best-effort deduplication feature of
	// BigQuery streaming inserts.
	//
	// If the InsertID is empty, a random insertID will be generated by
	// this library to facilitate deduplication.
	//
	// If the InsertID is set to the sentinel value NoDedupeID, an insertID
	// is not sent.
	//
	// For all other non-empty values, BigQuery will use the provided
	// value for best-effort deduplication.
	InsertID string

	Row []Value
}

ValuesSaver implements ValueSaver for a slice of Values.

func (*ValuesSaver) Save 

func (vls *ValuesSaver) Save() (map[string]Value, string, error)

Save implements ValueSaver.

Source Files

View all Source files

Directories

Path Synopsis
connection
apiv1
Package connection is an auto-generated package for the BigQuery Connection API.
 Package connection is an auto-generated package for the BigQuery Connection API.
apiv1beta1
Package connection is an auto-generated package for the BigQuery Connection API.
 Package connection is an auto-generated package for the BigQuery Connection API.
dataexchange
apiv1beta1
Package dataexchange is an auto-generated package for the Analytics Hub API.
 Package dataexchange is an auto-generated package for the Analytics Hub API.
datatransfer
apiv1
Package datatransfer is an auto-generated package for the BigQuery Data Transfer API.
 Package datatransfer is an auto-generated package for the BigQuery Data Transfer API.
Package internal is used to manage versioning of the released library.
 Package internal is used to manage versioning of the released library.
migration
apiv2
Package migration is an auto-generated package for the BigQuery Migration API.
 Package migration is an auto-generated package for the BigQuery Migration API.
apiv2alpha
Package migration is an auto-generated package for the BigQuery Migration API.
 Package migration is an auto-generated package for the BigQuery Migration API.
reservation
apiv1
Package reservation is an auto-generated package for the BigQuery Reservation API.
 Package reservation is an auto-generated package for the BigQuery Reservation API.
apiv1beta1
Package reservation is an auto-generated package for the BigQuery Reservation API.
 Package reservation is an auto-generated package for the BigQuery Reservation API.
storage
apiv1
Package storage is an auto-generated package for the BigQuery Storage API.
 Package storage is an auto-generated package for the BigQuery Storage API.
apiv1beta1
Package storage is an auto-generated package for the BigQuery Storage API.
 Package storage is an auto-generated package for the BigQuery Storage API.
apiv1beta2
Package storage is an auto-generated package for the BigQuery Storage API.
 Package storage is an auto-generated package for the BigQuery Storage API.
managedwriter
Package managedwriter provides an EXPERIMENTAL thick client around the BigQuery storage API's BigQueryWriteClient.
 Package managedwriter provides an EXPERIMENTAL thick client around the BigQuery storage API's BigQueryWriteClient.
managedwriter/adapt
Package adapt adds functionality related to converting bigquery representations like schema and data type representations.
 Package adapt adds functionality related to converting bigquery representations like schema and data type representations.

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