85dd265b7bb87fb19a9c8317fff97f24000367ee
- Fixes #246 - Bump up default parallelism to 1500, to handle large upserts - Add docs on s3 confuration & tuning tips with tested spark knobs - Fix bug to not duplicate hoodie metadata fields when input dataframe is another hoodie dataset - Improve speed of ROTablePathFilter by removing directory check - Move to spark-avro 4.0 to handle issue with nested fields with same name - Keep AvroConversionUtils in sync with spark-avro 4.0
Hudi
Hudi (pronounced Hoodie) stands for Hadoop Upserts anD Incrementals. Hudi manages storage of large analytical datasets on HDFS and serve them out via two types of tables
- Read Optimized Table - Provides excellent query performance via purely columnar storage (e.g. Parquet)
- Near-Real time Table (WIP) - Provides queries on real-time data, using a combination of columnar & row based storage (e.g Parquet + Avro)
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