pgsync 1.1.5

Postgres to elasticsearch sync

PostgreSQL to Elasticsearch sync

PGSync <https://pgsync.com>_ is a middleware for syncing data from Postgres <https://www.postgresql.org>_ to Elasticsearch <https://www.elastic.co/products/elastic-stack>.
It allows you to keep Postgres <https://www.postgresql.org> as your source of truth data source and expose structured denormalized documents in Elasticsearch <https://www.elastic.co/products/elastic-stack>_.

Requirements

• Python <https://www.python.org>_ 3.6+
• Postgres <https://www.postgresql.org>_ 9.4+
• Redis <https://redis.io>_
• Elasticsearch <https://www.elastic.co/products/elastic-stack>_ 6.3.1+

Postgres setup

Enable logical decoding <https://www.postgresql.org/docs/current/logicaldecoding.html>_ in your Postgres setting.

• you would also need to set up two parameters in your Postgres config postgresql.conf

  wal_level = logical

  max_replication_slots = 1

Installation

You can install PGSync from PyPI <https://pypi.org>_:

$ pip install pgsync

Config

Create a schema for the application named e.g schema.json

Example schema <https://github.com/toluaina/pg-sync/blob/master/examples/airbnb/schema.json>_

Example spec

.. code-block::

[
    {
        "database": "[database name]",
        "index": "[elasticsearch index]",
        "nodes": [
            {
                "table": "[table A]",
                "schema": "[table A schema]",
                "columns": [
                    "column 1 from table A",
                    "column 2 from table A",
                    ... additional columns
                ],
                "children": [
                    {
                        "table": "[table B with relationship to table A]",
                        "schema": "[table B schema]",
                        "columns": [
                          "column 1 from table B",
                          "column 2 from table B",
                          ... additional columns
                        ],
                        "relationship": {
                            "variant": "object",
                            "type": "one_to_many"
                        },
                        ...
                    },
                    {
                        ... any other additional children
                    }
                ]
            }
        ]
    }
]

Environment variables

Setup required environment variables for the application

SCHEMA='/path/to/schema.json'

ELASTICSEARCH_HOST=localhost
ELASTICSEARCH_PORT=9200

PG_HOST=localhost
PG_USER=i-am-root # this must be a postgres superuser
PG_PORT=5432
PG_PASSWORD=*****

REDIS_HOST=redis
REDIS_PORT=6379
REDIS_DB=0
REDIS_AUTH=*****

Running

bootstrap the database (one time only) $ bootstrap --config schema.json run pgsync as a daemon $ pgsync --config schema.json --daemon

======= History

1.0.1 (2020-15-01)

• First release on PyPI.

1.0.1 (2020-01-01)

• RC1 release

1.1.0 (2020-04-13)

• Postgres multi schema support for multi-tennant applications

• Show resulting Query with verbose mode

• this release required you to re-bootstrap your database with

  • bootstrap -t
  • bootstrap

1.1.1 (2020-05-18)

• Fixed authentication with Redis
• Fixed Docker build

1.1.2 (2020-06-11)

• Sync multiple indices in the same schema
• Test for replication or superuser
• Fix PG_NOTIFY error when payload exceeds 8000 bytes limit

1.1.3 (2020-06-14)

• Bug fix when syncing multiple indices in the same schema

1.1.4 (2020-06-15)

• Only create triggers for tables present in schema

1.1.5 (2020-06-16)

• Bug fix when creating multiple triggers in same schema