Github user MaxGekk commented on a diff in the pull request:
https://github.com/apache/spark/pull/20959#discussion_r180537052
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala ---
@@ -528,6 +529,7 @@ class DataFrameReader private[sql](sparkSession:
SparkSession) extends Logging {
* <li>`header` (default `false`): uses the first line as names of
columns.</li>
* <li>`inferSchema` (default `false`): infers the input schema
automatically from data. It
* requires one extra pass over the data.</li>
+ * <li>`samplingRatio` (default 1.0): the sample ratio of rows used for
schema inferring.</li>
--- End diff --
I just did absolutely the same as `samplingRatio` for JSON datasource -
`samplingRatio` is not supported as a parameter of `json()` but could be set as
the option like `.option('samplingRatio', '0.1')`. Should I update PySpark
API regarding `samplingRatio` for `json()` in separate PR?
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