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Postgres to elasticsearch sync

Project description

# PostgreSQL to Elasticsearch sync

PGSync is a middleware for syncing data from Postgres to Elasticsearch. It allows you to keep Postgres as your source of truth data source and expose structured denormalized documents in Elasticsearch.

### Requirements

### Postgres setup

Enable logical decoding in your Postgres setting.

  • you would also need to set up at least two parameters at 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

        "index": "[database name]",
        "nodes": [
                "table": "[table A]",
                "columns": [
                    "column 1 from table A",
                    "column 2 from table A",
                    ... additional columns
                "children": [
                        "table": "[table B with relationship to table A]",
                        "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



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


## Running

bootstrap the database (one time only)

$ bootstrap –config schema.json

run pgsync as a daemon

$ pgsync –config schema.json –daemon


1.0.1 (2020-15-01)

  • First release on PyPI.

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