Github user holdenk commented on a diff in the pull request: https://github.com/apache/spark/pull/17077#discussion_r115129876 --- Diff: python/pyspark/sql/readwriter.py --- @@ -563,6 +563,60 @@ def partitionBy(self, *cols): self._jwrite = self._jwrite.partitionBy(_to_seq(self._spark._sc, cols)) return self + @since(2.3) + def bucketBy(self, numBuckets, *cols): + """Buckets the output by the given columns on the file system. + + :param numBuckets: the number of buckets to save + :param cols: name of columns + + .. note:: Applicable for file-based data sources in combination with + :py:meth:`DataFrameWriter.saveAsTable`. + + >>> (df.write.format('parquet') + ... .bucketBy(100, 'year', 'month') + ... .mode("overwrite") + ... .saveAsTable('bucketed_table')) + """ + if len(cols) == 1 and isinstance(cols[0], (list, tuple)): + cols = cols[0] + + if not isinstance(numBuckets, int): + raise TypeError("numBuckets should be an int, got {0}.".format(type(numBuckets))) + + if not all(isinstance(c, basestring) for c in cols): + raise TypeError("cols argument should be a string or a sequence of strings.") --- End diff -- So I don't think we really support all sequences (the above typecheck on L581 requires list or tuple but there are additional types of sequences).
--- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org