João Pedro Jericó created SPARK-20294: -----------------------------------------
Summary: _inferSchema for RDDs fails if sample returns empty RDD Key: SPARK-20294 URL: https://issues.apache.org/jira/browse/SPARK-20294 Project: Spark Issue Type: Bug Components: PySpark Affects Versions: 2.1.0 Reporter: João Pedro Jericó Priority: Minor Currently the _inferSchema function on [session.py](https://github.com/apache/spark/blob/master/python/pyspark/sql/session.py#L354) line 354 fails if applied to an RDD for which the sample call returns an empty RDD. This is possible for example if one has a small RDD but that needs the schema to be inferred by more than one Row. For example: ```python small_rdd = sc.parallelize([(1, 2), (2, 'foo')]) small_rdd.toDF(samplingRatio=0.01).show() ``` This will fail with high probability because when sampling the small_rdd with the .sample method will return an empty RDD most of the time. However, this is not the desired result because we are able to sample at least 1% of the RDD. -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org