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Collection of transforms for the Apache beam python SDK.

Project description

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About

A collection of random transforms for the Apache beam python SDK . Many are simple transforms. The most useful ones are those for reading/writing from/to relational databases.

Installation

  • Using pip
pip install beam-nuggets
  • From source
git clone git@github.com:mohaseeb/beam-nuggets.git
cd beam-nuggets
pip install .

Supported transforms

IO

Others

Documentation

See here.

Usage

Write data to an SQLite table using beam-nugget's relational_db.Write transform.

# write_sqlite.py contents
import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
from beam_nuggets.io import relational_db

records = [
    {'name': 'Jan', 'num': 1},
    {'name': 'Feb', 'num': 2}
]

source_config = relational_db.SourceConfiguration(
    drivername='sqlite',
    database='/tmp/months_db.sqlite',
    create_if_missing=True  # create the database if not there 
)

table_config = relational_db.TableConfiguration(
    name='months',
    create_if_missing=True,  # automatically create the table if not there
    primary_key_columns=['num']  # and use 'num' column as primary key
)
    
with beam.Pipeline(options=PipelineOptions()) as p:  # Will use local runner
    months = p | "Reading month records" >> beam.Create(records)
    months | 'Writing to DB' >> relational_db.Write(
        source_config=source_config,
        table_config=table_config
    )

Execute the pipeline

python write_sqlite.py 

Examine the contents

sqlite3 /tmp/months_db.sqlite 'select * from months'
# output:
# 1.0|Jan
# 2.0|Feb

To write the same data to a PostgreSQL table instead, just create a suitable relational_db.SourceConfiguration as follows.

source_config = relational_db.SourceConfiguration(
    drivername='postgresql+pg8000',
    host='localhost',
    port=5432,
    username='postgres',
    password='password',
    database='calendar',
    create_if_missing=True  # create the database if not there 
)

Click here for more examples, including writing to PostgreSQL in Google Cloud Platform using the DataFlowRunner.

An example showing how you can use beam-nugget's relational_db.ReadFromDB transform to read from a PostgreSQL database table.

from __future__ import print_function
import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
from beam_nuggets.io import relational_db

with beam.Pipeline(options=PipelineOptions()) as p:
    source_config = relational_db.SourceConfiguration(
        drivername='postgresql+pg8000',
        host='localhost',
        port=5432,
        username='postgres',
        password='password',
        database='calendar',
    )
    records = p | "Reading records from db" >> relational_db.ReadFromDB(
        source_config=source_config,
        table_name='months',
        query='select num, name from months'  # optional. When omitted, all table records are returned. 
    )
    records | 'Writing to stdout' >> beam.Map(print)

See here for more examples.

Development

  • Install
git clone git@github.com:mohaseeb/beam-nuggets.git
cd beam-nuggets
export BEAM_NUGGETS_ROOT=`pwd`
pip install -e .[dev]
  • Make changes on dedicated dev branches
  • Run tests
cd $BEAM_NUGGETS_ROOT
python -m unittest discover -v
  • Generate docs
cd $BEAM_NUGGETS_ROOT
docs/generate_docs.sh
  • Create a PR against master.
  • After merging the accepted PR and updating the local master, upload a new build to pypi.
cd $BEAM_NUGGETS_ROOT
scripts/build_test_deploy.sh

Backlog

  • versioned docs?
  • Summarize the investigation of using Source/Sink Vs ParDo(and GroupBy) for IO
  • more nuggets: WriteToCsv
  • Investigate readiness of SDF ParDo, and possibility to use for relational_db.ReadFromDB
  • integration tests
  • DB transforms failures handling on IO transforms
  • more nuggets: Elasticsearch, Mongo
  • WriteToRelationalDB, logging

Contributions by

mohaseeb, astrocox, 2514millerj, alfredo, shivangkumar

Licence

MIT

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