Github user zero323 commented on a diff in the pull request: https://github.com/apache/spark/pull/17077#discussion_r115133626 --- 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 -- Good point. We can support arbitrary `Iterable[str]` though. ```python if len(cols) == 1 and isinstance(cols[0], collections.abc.Iterable): cols = list(cols[0]) ``` Caveat is, we don't allow this anywhere else.
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