The target-postgres Singer target sends data into PostgreSQL database after it was pulled from a source using a Singer tap.

Alternative variants

Multiple variants of target-postgres are available. This document describes the transferwise variant.

Alternative variants are:

Standalone usage

Install the package using pip:

pip install pipelinewise-target-postgres

For additional instructions, refer to the README in the repository.

Usage with Meltano

Install Meltano, create your Meltano project, and add the target to your project as a loader:

meltano add loader target-postgres --variant transferwise

For additional instructions, refer to the Meltano-specific documentation for target-postgres.

Capabilities

Settings

host

PostgreSQL host

port

PostgreSQL port

user

PostgreSQL user

password

PostgreSQL password

dbname

PostgreSQL database name

ssl

default_target_schema

Name of the schema where the tables will be created. If schema_mapping is not defined then every stream sent by the tap is loaded into this schema.

batch_size_rows

Maximum number of rows in each batch. At the end of each batch, the rows in the batch are loaded into Postgres.

flush_all_streams

Flush and load every stream into Postgres when one batch is full. Warning: This may trigger the COPY command to use files with low number of records.

parallelism

The number of threads used to flush tables. 0 will create a thread for each stream, up to parallelism_max. -1 will create a thread for each CPU core. Any other positive number will create that number of threads, up to parallelism_max.

parallelism_max

Max number of parallel threads to use when flushing tables.

default_target_schema_select_permission

Grant USAGE privilege on newly created schemas and grant SELECT privilege on newly created tables to a specific role or a list of roles. If schema_mapping is not defined then every stream sent by the tap is granted accordingly.

schema_mapping

Useful if you want to load multiple streams from one tap to multiple Postgres schemas. If the tap sends the stream_id in <schema_name>-<table_name> format then this option overwrites the default_target_schema value. Note, that using schema_mapping you can overwrite the default_target_schema_select_permission value to grant SELECT permissions to different groups per schemas or optionally you can create indices automatically for the replicated tables.

add_metadata_columns

Metadata columns add extra row level information about data ingestions, (i.e. when was the row read in source, when was inserted or deleted in postgres etc.) Metadata columns are creating automatically by adding extra columns to the tables with a column prefix _SDC_. The column names are following the stitch naming conventions documented at https://www.stitchdata.com/docs/data-structure/integration-schemas#sdc-columns. Enabling metadata columns will flag the deleted rows by setting the _SDC_DELETED_AT metadata column. Without the add_metadata_columns option the deleted rows from singer taps will not be recongisable in Postgres.

hard_delete

When hard_delete option is true then DELETE SQL commands will be performed in Postgres to delete rows in tables. It’s achieved by continuously checking the _SDC_DELETED_AT metadata column sent by the singer tap. Due to deleting rows requires metadata columns, hard_delete option automatically enables the add_metadata_columns option as well.

data_flattening_max_level

Object type RECORD items from taps can be transformed to flattened columns by creating columns automatically. When value is 0 (default) then flattening functionality is turned off.

primary_key_required

Log based and Incremental replications on tables with no Primary Key cause duplicates when merging UPDATE events. When set to true, stop loading data if no Primary Key is defined.

validate_records

Validate every single record message to the corresponding JSON schema. This option is disabled by default and invalid RECORD messages will fail only at load time by Postgres. Enabling this option will detect invalid records earlier but could cause performance degradation.

temp_dir

(Default: platform-dependent) Directory of temporary CSV files with RECORD messages.

Looking for help?

If you're having trouble getting target-postgres to work by itself or with Meltano, look for an existing issue in its repository, file a new issue, or join the Meltano Slack community and ask for help in the #plugins-general channel.

Found an issue on this page?

This page is generated from a YAML file that you can contribute changes to! It is also validated against a JSON Schema used for taps and targets.