README ¶
pgfutter
Import CSV and JSON into PostgreSQL the easy way. This small tool abstract all the hassles and swearing you normally have to deal with when you just want to dump some data into the database.
Features:
- Generated import tables (
pgfutter csv <file>
and your done) - Good performance using the
COPY
streaming protocol - Easy deployment
- Dealing with import errors
- Import over the network
Install
You can download a single binary for Linux, OSX or Windows.
OSX
wget -O pgfutter https://github.com/lukasmartinelli/pgfutter/releases/download/v0.3.1/pgfutter_darwin_amd64
chmod +x pgfutter
./pgfutter --help
Linux
wget -O pgfutter https://github.com/lukasmartinelli/pgfutter/releases/download/v0.3.1/pgfutter_linux_amd64
chmod +x pgfutter
./pgfutter --help
Install from source
go get github.com/lukasmartinelli/pgfutter
If you are using Windows or 32-bit architectures you need to download the appropriate binary yourself.
Import CSV
pgfutter
will deal with CSV files conforming to RFC 4180.
Create friends.csv
.
name,age,friends
Jacob,26,"Anthony"
Anthony,25,""
Emma,28,"Jacob,Anthony"
Import the CSV file.
pgfutter csv friends.csv
Because header rows are already provided pgfutter
will create the appropriate
table and copy the rows.
name | age | friends |
---|---|---|
Jacob | 26 | Anthony |
Anthony | 25 | |
Emma | 28 | Jacob,Anthony |
pgfutter
will only help you to get the data into the database. After that
SQL is a great language to sanitize and normalize the data according to your desired database schema.
CREATE TABLE public.person (
name VARCHAR(200) PRIMARY KEY,
age INTEGER
)
CREATE TABLE public.friendship (
person VARCHAR(200) REFERENCES public.person(name),
friend VARCHAR(200) REFERENCES public.person(name)
)
INSERT INTO public.person
SELECT name, age::int
FROM import.friends
WITH friends AS
(SELECT name as person, regexp_split_to_table(friends, E'\\,') AS friend
FROM import.friends)
INSERT INTO public.friendship
SELECT * FROM
friends WHERE friend <> ''
Import JSON
A lot of event logs contain JSON objects nowadays (e.g. GitHub Archive).
pgfutter
expects each line to have a valid JSON object. Importing JSON is only supported for Postgres 9.3 and Postgres 9.4 due to the JSON
type.
Create friends.json
.
{"name": "Jacob", "age": 26, "friends": ["Anthony"]}
{"name": "Anthony", "age": 25, "friends": []}
{"name": "Emma", "age": 28, "friends": ["Jacob", "Anthony"]}
Import the JSON file.
pgfutter json friends.json
Your JSON objects will be stored in a single JSON column called data
.
data |
---|
{"name": "Jacob", "age": 26, "friends": ["Anthony"]} |
{"name": "Anthony", "age": 25, "friends": []} |
{"name": "Emma", "age": 28, "friends": ["Jacob", "Anthony"]} |
PostgreSQL has excellent JSON support which means you can then start normalizing your data.
CREATE TABLE public.person (
name VARCHAR(200) PRIMARY KEY,
age INTEGER
)
CREATE TABLE public.friendship (
person VARCHAR(200) REFERENCES public.person(name),
friend VARCHAR(200) REFERENCES public.person(name)
)
INSERT INTO public.person
SELECT data->>'name' as name, (data->>'age')::int as age
FROM import.friends
INSERT INTO public.friendship
SELECT data->>'name' as person, json_array_elements_text(data->'friends')
FROM import.friends
Database Connection
Database connection details can be provided via environment variables or as separate flags.
name | default | description |
---|---|---|
DB_NAME |
postgres |
database name |
DB_HOST |
localhost |
host name |
DB_PORT |
5432 |
port |
DB_SCHEMA |
import |
schema to create tables for |
DB_USER |
postgres |
database user |
DB_PASS |
password (or empty if none) |
Advanced Use Cases
Custom delimiter
Quite often you want to specify a custom delimiter (default: ,
).
pgfutter csv -d "\t" traffic_violations.csv
You have to use "
as a quoting character and \
as escape character.
You might omit the quoting character if it is not necessary.
Custom header fields
If you want to specify the field names explicitly you can skip the header row and pass a comma separated field name list.
pgfutter csv --skip-header --fields "name,state,year" traffic_violations.csv
If you don't have a header row in a document you should specify the field names as well.
pgfutter csv --fields "name,state,year" traffic_violations.csv
Encoding
All CSV files need to be utf-8
encoded. No other encoding is supported.
Encoding is a nasty topic and you should deal with it before it enters
the database.
Dealing with invalid input
A lot of CSV files don't confirm to proper CSV standards. If you want
to ignore errors you can pass the --ignore-errors
flag which will
commit the transaction even if some rows cannot be imported.
The failed rows will be written to stdout so you can clean them up with other tools.
pgfutter --ignore-errors csv traffic_violations.csv 2> traffic_violations_errors.csv
This works the same for invalid JSON objects.
Custom Table
pgfutter
will take the sanitized filename as the table name. If you want to specify a custom table name or import into your predefined table schema you can specify the table explicitly.
pgfutter csv --table violations traffic_violations.csv
Alternatives
For more sophisticated needs you should take a look at pgloader.
Regression Tests
The program is tested with open data sets from around the world.
Download all samples into the folder samples
.
./download-samples.sh
Run import regression tests against the samples.
./test.sh
Cross-compiling
We use gox to create distributable binaries for Windows, OSX and Linux.
docker run --rm -v "$(pwd)":/usr/src/pgfutter -w /usr/src/pgfutter tcnksm/gox:1.4.2-light
Documentation ¶
There is no documentation for this package.