Github user dilipbiswal commented on a diff in the pull request: https://github.com/apache/spark/pull/20525#discussion_r167159534 --- Diff: docs/sql-programming-guide.md --- @@ -1930,6 +1930,9 @@ working with timestamps in `pandas_udf`s to get the best performance, see - Literal values used in SQL operations are converted to DECIMAL with the exact precision and scale needed by them. - The configuration `spark.sql.decimalOperations.allowPrecisionLoss` has been introduced. It defaults to `true`, which means the new behavior described here; if set to `false`, Spark uses previous rules, ie. it doesn't adjust the needed scale to represent the values and it returns NULL if an exact representation of the value is not possible. + - Since Spark 2.3, writing an empty dataframe (a dataframe with 0 partitions) in parquet or orc format, creates a format specific metadata only file. In prior versions the metadata only file was not created. As a result, subsequent attempt to read from this directory fails with AnalysisException while inferring schema of the file. For example : df.write.format("parquet").save("outDir") --- End diff -- even -> even if ? self-described -> self-describing ? @cloud-fan Nicely written. Thanks. Let me know if you are ok with the above two change ?
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