[GitHub] [spark] gatorsmile commented on a change in pull request #24518: [SPARK-27627][SQL] Make option "pathGlobFilter" as a general option for all file sources

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gatorsmile commented on a change in pull request #24518: [SPARK-27627][SQL] Make option "pathGlobFilter" as a general option for all file sources
URL: https://github.com/apache/spark/pull/24518#discussion_r280829502
 
 

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 File path: docs/sql-migration-guide-upgrade.md
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 @@ -126,6 +126,8 @@ license: |
 
   - Since Spark 3.0, parquet logical type `TIMESTAMP_MICROS` is used by default while saving `TIMESTAMP` columns. In Spark version 2.4 and earlier, `TIMESTAMP` columns are saved as `INT96` in parquet files. To set `INT96` to `spark.sql.parquet.outputTimestampType` restores the previous behavior.
 
+  - Since Spark 3.0, a new data source option `pathGlobFilter` is introduced for filtering files in `DataFrameReader` and `DataStreamReader`. For example, `spark.read.option("pathGlobFilter", "*.orc").orc(path)` will read all the files ending with `.orc` under the given `path`. Note that with the option the query result will contain partition columns if any; while with glob pattern in path, e.g `spark.read.orc("path/*/*/*/*.orc")`, the result won't contain partition columns.
 
 Review comment:
   This does not introduce any behavior change. Thus, I would prefer to document it in the SQL guide: https://spark.apache.org/docs/latest/sql-data-sources-load-save-functions.html 
   
   I think we can add a section for documenting the useful options for our built-in file sources. 

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