Conduit Connector Snowflake
General
The Snowflake connector is one of Conduit plugins. It provides the source
snowflake connector.
Prerequisites
Configuration
Source
The config passed to Configure
can contain the following fields.
name |
description |
required |
example |
connection |
Snowflake connection string. Important: Schema is required. |
true |
"user:password@my_organization-my_account/mydb/schema" or "username[:password]@hostname:port/dbname/schemaname" |
table |
The table the connector will read records from. |
true |
"users" |
columns |
Comma-separated list of column names that should be included in each record payload. Default is false which translates to All columns . |
false |
"id,name,age" |
primaryKeys |
Comma-separated list of column that records should use for their Key fields. |
false |
"id,name" |
orderingColumn |
The column name the connector will use for ordering rows. Important: Values must be unique and suitable for sorting. Otherwise, the snapshot will not work. |
true |
"id" |
snapshot |
Whether or not the plugin will take a snapshot of the entire table before starting cdc mode. Default is true . Other possible value is false . |
false |
"false" |
batchSize |
Size of batch. Important: Please don't update this variable after the pipeline starts, it will cause problems with tracking position. Default is 1000 . |
false |
"1000" |
Destination
name |
description |
required |
example |
username |
Snowflake username. |
true |
"username" |
password |
Snowflake password. |
true |
"password" |
host |
Snowflake host. |
true |
"https://mycompany.us-west-2.snowflakecomputing.com" |
database |
Snowflake database. |
true |
"userdb" |
schema |
Snowflake schema. |
true |
"STREAM_DATA" |
warehouse |
Snowflake warehouse. |
true |
"COMPUTE_WH" |
stage |
Snowflake stage to use for uploading files before merging into destination table. |
true |
"ordersStage" |
primaryKey |
Primary key of the source data. |
true |
"id" |
namingPrefix |
Prefix to append to updated_at , deleted_at , created_at in destination table. Default is meroxa_ , translates to meroxa_updated_at for update timestamps. |
false |
"meroxa" |
format |
Data type of file we upload and copy data from to Snowflake. Default is csv and cannot be changed until additional formats are supported. |
true |
"csv" |
compression |
Compression to use when staging files in Snowflake. Default is zstd . Other possible values are gzip and copy . |
false |
"zstd" |
sdk.batch.size |
Maximum size of batch before it gets written to Snowflake. Default is 1000 . |
false |
"1000" |
sdk.batch.delay |
Maximum delay before an incomplete batch is written to the destination. |
false |
5s |
csvGoRoutines |
For CSV processing, the number of goroutines to concurrently process CSV rows. Default is 1 . |
false |
1 |
fileUploadThreads |
Number of threads to run for PUT file uploads. Default is 30 . |
false |
30 |
keepAlive |
Whether to keep the session alive even when the connection is idle. Default is true . |
false |
true |
How to build it
Run make build
.
Testing
Run make test
.
Snowflake Source
Snapshot Iterator
When the connector first starts, snapshot mode is enabled.
A "snapshot" is the state of a table data at a particular point in time when connector starts work. All changes after this
(delete, update, insert operations) will be captured by the Change Data Capture (CDC) iterator.
First time when the snapshot iterator starts work, it is get max value from orderingColumn
and saves this value to position.
The snapshot iterator reads all rows, where orderingColumn
values less or equal maxValue, from the table in batches
via SELECT with fetching and ordering by orderingColumn
.
OrderingColumn
value must be unique and suitable for sorting, otherwise, the snapshot won't work correctly.
Iterators saves last processed value from orderingColumn
column to position to field SnapshotLastProcessedVal
.
If snapshot stops it will parse position from last record and will try gets row where {{orderingColumn}} > {{position.SnapshotLastProcessedVal}}
When all records are returned, the connector switches to the CDC iterator.
This behavior is enabled by default, but can be turned off by adding "snapshot":"false" to the Source configuration.
CDC Iterator
The CDC iterator starts working if snapshot iterator method HasNext
return false.
The CDC iterator uses snowflake 'stream' (more information about streams
https://docs.snowflake.com/en/user-guide/streams-intro.html).
The change tracking system utilized by the stream
then records information about the
DML changes after this snapshot was taken. Change records provide the state
of a row before and after the change. Change information mirrors the column structure
of the tracked source object and includes additional metadata columns that describe each change event.
Stream
itself does not contain any table data. When we add new row to table after stream creation or stream consuming
this row will be added to stream table. If this row will be removed, this row will be removed from stream table
When row was added to table before stream creation or stream consuming it is not exist in stream table.
If this row will be removed, we will get record about it in stream table.
Stream
has columns:
METADATA$ACTION
: Indicates the DML operation (INSERT, DELETE) recorded.
METADATA$ISUPDATE
: Indicates whether the operation was part of an UPDATE statement.
Updates to rows in the source object are represented as a pair of DELETE and
INSERT records in the stream with a metadata column METADATA$ISUPDATE values set to TRUE.
METADATA$ROW_ID
: Specifies the unique and immutable ID for the row, which can be used to track changes
to specific rows over time.
When source starts work first time iterator creates stream with name conduit_stream_{table}
to table
from
config, creates table with name conduit_tracking_{table}
. Table uses for consuming stream and ability to resume
CDC iterator after interrupting.
This table has the same schema as table
with additional metadata columns:
METADATA$ACTION
, METADATA$ISUPDATE
, METADATA$ROW_ID
(Those columns from stream) and METADATA$TS
.
METADATA$TS
it is timestamp column, it is special column created by iterator to ordering rows from tracking table.
When iterator consume data from stream using insert query to consuming table. METADATA$TS
will have current timestamp value.
After consuming stream, tracking table has copy of stream data with inserted time. All rows from stream were
automatically removed and stream did new snapshot for table
.
Iterator run select query for getting data from consuming table using limit and offset and ordering by METADATA$TS
.
Batch size is configurable, offset value is zero for first time.
Iterator save information from table to currentBatch
slice variable. Iterator HasNext
method check if next element
exist in currentBatch
using variable index
and if it is needed change offset and run select query to get new data
with new offset. Method Next
gets next element converts it to Record
checks action(can be insert
, delete
, update
)
using metadata columns METADATA$ACTION
, METADATA$ISUPDATE
. Iterator increases index
and tries to find next record.
For example, we have table with name CLIENTS
and fields ID
, NAME
. Connector creates
stream with name CONDUIT_STREAM_CLIENTS
and creates tracking table with name CONDUIT_TRACKING_CLIENTS
with fields:
ID
,NAME
, METADATA$ACTION
, METADATA$ISUPDATE
, METADATA$ROW_ID
, METADATA$TS
. We remove row with id = 2, which
was inserted before stream creation we get row in CONDUIT_STREAM_CLIENTS
.
ID |
NAME |
METADATA$ACTION |
METADATA$ISUPDATE |
METADATA$ROW_ID |
2 |
Test |
DELETE |
FALSE |
fafe92c9c207a714bfbf8ef55e32c501852b5c8e |
Then we add new client. Stream table will look like:
ID |
NAME |
METADATA$ACTION |
METADATA$ISUPDATE |
METADATA$ROW_ID |
5 |
Foo |
INSERT |
FALSE |
ef465fb7a243abcb3ef019b6c5ce89d490218b11 |
2 |
Test |
DELETE |
FALSE |
fafe92c9c207a714bfbf8ef55e32c501852b5c8e |
Connector consumes stream running query INSERT INTO CONDUIT_TRACKING_CLIENTS SELECT *, current_timestamp() FROM CONDUIT_STREAM_CLIENTS
. After this stream will be empty, we will have data on tracking table.
The connector will run select query:
SELECT * FROM CONDUIT_TRACKING_CLIENTS ORDER BY METADATA$TS LIMIT {batchSize} OFFSET 0;
Connectors will transform this data to records.
NOTE: please pay attention and don't accidentally delete stream
and tracking table were created by CDC iterator.
Snowflake Destination
The Snowflake Destination is still in early stages of development - please use with caution as we are still improving it for initial release.