Light IO transforms for Postgres read/write in Apache Beam pipelines.
The project aims to provide highly performant and customizable transforms and is not intended to support many different SQL database engines.
ReadAllFromPostgres,ReadFromPostgres`` andWriteToPostgres` transforms- Records can be mapped to tuples, dictionaries or dataclasses
- Reads and writes are in configurable batches
Printing data from the database table:
import apache_beam as beam
from psycopg.rows import dict_row
from beam_postgres.io import ReadAllFromPostgres
with beam.Pipeline() as p:
data = p | "Reading example records from database" >> ReadAllFromPostgres(
"host=localhost dbname=examples user=postgres password=postgres",
"select id, data from source",
dict_row,
)
data | "Writing to stdout" >> beam.Map(print)Writing data to the database table:
from dataclasses import dataclass
import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
from beam_postgres.io import WriteToPostgres
@dataclass
class Example:
data: str
with beam.Pipeline(options=PipelineOptions()) as p:
data = p | "Reading example records" >> beam.Create(
[
Example("example1"),
Example("example2"),
]
)
data | "Writing example records to database" >> WriteToPostgres(
"host=localhost dbname=examples user=postgres password=postgres",
"insert into sink (data) values (%(data)s)",
)See here for more examples.
There may be situations when you have so much data that it will not fit into the memory - then you want to read your table data in batches. You can see an example code here (the code reads records in a batches of 1).