Skip to main content

Postgres to Elasticsearch/OpenSearch sync

Project description

PostgreSQL to Elasticsearch/OpenSearch sync

Requirements

Postgres setup

Enable logical decoding in your Postgres setting.

  • You 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:

$ pip install pgsync

Config

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

Example schema

Example spec

.. code-block::

[
    {
        "database": "[database name]",
        "index": "[Elasticsearch or OpenSearch 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"
                    },
                    ...
                },
                {
                    ... additional children
                }
            ]
        }
    }
]

Environment variables

Setup environment variables required 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 or replication user
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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pgsync-3.1.0.tar.gz (112.7 kB view details)

Uploaded Source

Built Distribution

pgsync-3.1.0-py3-none-any.whl (60.3 kB view details)

Uploaded Python 3

File details

Details for the file pgsync-3.1.0.tar.gz.

File metadata

  • Download URL: pgsync-3.1.0.tar.gz
  • Upload date:
  • Size: 112.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.1

File hashes

Hashes for pgsync-3.1.0.tar.gz
Algorithm Hash digest
SHA256 50b90bc61cd37f1ff9d45ea5f5b74b64f409b2d9725c1e6a05ea0b71220b40b5
MD5 dae019e447e16eb2a0115a178de02bec
BLAKE2b-256 67daab3b9c118da84dcd0b67a7dc1b3aac7a51bbb5c7d2be58db709ea32b3d3e

See more details on using hashes here.

File details

Details for the file pgsync-3.1.0-py3-none-any.whl.

File metadata

  • Download URL: pgsync-3.1.0-py3-none-any.whl
  • Upload date:
  • Size: 60.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.1

File hashes

Hashes for pgsync-3.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f6183d51adeb5ac0dc3ab9620d1c21f32afc5cc38b4baf013fa61b157f55976b
MD5 c27adedf0b3ed3722a4376f51bcff448
BLAKE2b-256 0006d7f1d995aaa18f5f8abbf246932e7a70fd84a673c48b017e9e76e5484b41

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page