Package: pipelinewise-target-postgres
pipelinewise-target-postgresSingertarget that loads data into PostgreSQL following theSinger spec.This is aPipelineWisecompatible target connector.How to use itThe recommended method of running this target is to use it fromPipelineWise. When running it from PipelineWise you don't need to configure this tap with JSON files and most of things are automated. Please check the related documentation atTarget PostgresIf you want to run thisSinger Targetindependently please read further.InstallFirst, make sure Python 3 is installed on your system or follow these
installation instructions forMacorUbuntu.It's recommended to use a virtualenv:makevenvTo runLike any other target that's following the singer specification:some-singer-tap | target-postgres --config [config.json]It's reading incoming messages from STDIN and using the properties inconfig.jsonto upload data into Postgres.Note: To avoid version conflicts runtapandtargetsin separate virtual environments.Spin up a PG DBMake use of the available docker-compose file to spin up a PG DB.docker-composeup-d--builddbConfiguration settingsRunning the target connector requires aconfig.jsonfile. An example with the minimal settings:{"host":"localhost","port":5432,"user":"my_user","password":"secret","dbname":"target_db","default_target_schema":"public"}Full list of options inconfig.json:PropertyTypeRequired?DescriptionhostStringYesPostgreSQL hostportIntegerYesPostgreSQL portuserStringYesPostgreSQL userpasswordStringYesPostgreSQL passworddbnameStringYesPostgreSQL database namebatch_size_rowsInteger(Default: 100000) Maximum number of rows in each batch. At the end of each batch, the rows in the batch are loaded into Postgres.flush_all_streamsBoolean(Default: False) 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.parallelismInteger(Default: 0) 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.max_parallelismInteger(Default: 16) Max number of parallel threads to use when flushing tables.default_target_schemaStringName of the schema where the tables will be created. Ifschema_mappingis not defined then every stream sent by the tap is loaded into this schema.default_target_schema_select_permissionStringGrant USAGE privilege on newly created schemas and grant SELECT privilege on newly createdschema_mappingObjectUseful if you want to load multiple streams from one tap to multiple Postgres schemas.If the tap sends thestream_idin<schema_name>-<table_name>format then this option overwrites thedefault_target_schemavalue. Note, that usingschema_mappingyou can overwrite thedefault_target_schema_select_permissionvalue to grant SELECT permissions to different groups per schemas or optionally you can create indices automatically for the replicated tables.Note: This is an experimental feature and recommended to use via PipelineWise YAML files that will generate the object mapping in the right JSON format. For further info check aPipelineWise YAML Example.add_metadata_columnsBoolean(Default: False) 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 athttps://www.stitchdata.com/docs/data-structure/integration-schemas#sdc-columns. Enabling metadata columns will flag the deleted rows by setting the_SDC_DELETED_ATmetadata column. Without theadd_metadata_columnsoption the deleted rows from singer taps will not be recognisable in Postgres.hard_deleteBoolean(Default: False) Whenhard_deleteoption 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_ATmetadata column sent by the singer tap. Due to deleting rows requires metadata columns,hard_deleteoption automatically enables theadd_metadata_columnsoption as well.data_flattening_max_levelInteger(Default: 0) 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_requiredBoolean(Default: True) 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_recordsBoolean(Default: False) 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_dirString(Default: platform-dependent) Directory of temporary CSV files with RECORD messages.To run tests:Define environment variables that requires running the testsexport TARGET_POSTGRES_HOST=<postgres-host>
  export TARGET_POSTGRES_PORT=<postgres-port>
  export TARGET_POSTGRES_USER=<postgres-password>
  export TARGET_POSTGRES_PASSWORD=<postgres-password>
  export TARGET_POSTGRES_DBNAME=<postgres-dbname>
  export TARGET_POSTGRES_SCHEMA=<postgres-schema>PS: You can runmake envto export pre-defined environment variablesInstall python dependencies in a virtual env and run unit and integration testsmake venvTo run unit tests:make unit_testTo run integration tests:make integration_testTo run pylint:Install python dependencies and run python lintermake venv pylintLicenseApache License Version 2.0SeeLICENSEto see the full text.