Hello postgres users,
Spark-postgres is designed for reliable and performant ETL in big-data
workload and offers read/write/scd capability to better bridge spark and
postgres. The version 3 introduces a datasource API. It outperforms
sqoop by factor 8 and the apache spark core jdbc by infinity.
Features:
- use of pg COPY statements
- parallel reads/writes
- use of hdfs to store intermediary csv
- reindex after bulk-loading
- SCD1 computations done on the spark side
- use unlogged tables when needed
- handle arrays and multiline string columns
- useful jdbc functions (ddl, updates...)
The official repository:
https://framagit.org/parisni/spark-etl/tree/master/spark-postgres
And its mirror on microsoft github:
https://github.com/EDS-APHP/spark-etl/tree/master/spark-postgres
--
nicolas
