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From marmbrus <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-14555] First cut of Python API for Stru...
Date Fri, 15 Apr 2016 18:20:50 GMT
Github user marmbrus commented on a diff in the pull request:

    https://github.com/apache/spark/pull/12320#discussion_r59917973
  
    --- Diff: python/pyspark/sql/readwriter.py ---
    @@ -426,6 +488,68 @@ def save(self, path=None, format=None, mode=None, partitionBy=None,
**options):
             else:
                 self._jwrite.save(path)
     
    +    @ignore_unicode_prefix
    +    @since(2.0)
    +    def startStream(self, path=None, format=None, mode=None, partitionBy=None,
    +                    queryName=None, checkpointLocation=None, trigger=None, **options):
    +        """Saves the contents of the :class:`DataFrame` to a data source.
    +
    +        The data source is specified by the ``format`` and a set of ``options``.
    +        If ``format`` is not specified, the default data source configured by
    +        ``spark.sql.sources.default`` will be used.
    +
    +        :param path: the path in a Hadoop supported file system
    +        :param format: the format used to save
    +        :param mode: specifies the behavior of the save operation when data already exists.
    +
    +            * ``append``: Append contents of this :class:`DataFrame` to existing data.
    +            * ``overwrite``: Overwrite existing data.
    +            * ``ignore``: Silently ignore this operation if data already exists.
    +            * ``error`` (default case): Throw an exception if data already exists.
    +        :param partitionBy: names of partitioning columns
    +        :param queryName: unique name for the query
    +        :param trigger: Set the trigger for the stream query. The default value is
    +           `ProcessingTime(0)` and it will run as fast as possible.
    +        :param checkpointLocation: An optional location for checkpointing state and metadata.
    +        :param options: all other string options
    +
    +        >>> temp = tempfile.mkdtemp()
    +        >>> cq = sdf.write.format('text').startStream(os.path.join(temp, 'out'),
    +        ...     checkpointLocation=os.path.join(temp, 'chk'))
    +        >>> cq.isActive
    +        True
    +        >>> cq.stop()
    +        >>> cq.isActive
    +        False
    +        >>> from pyspark.sql.streaming import ProcessingTime
    +        >>> cq = sdf.write.startStream(os.path.join(temp, 'out'), format='text',
    +        ...     queryName='my_query', trigger=ProcessingTime('5 seconds'),
    +        ...     checkpointLocation=os.path.join(temp, 'chk'))
    +        >>> cq.name
    +        u'my_query'
    +        >>> cq.isActive
    +        True
    +        >>> cq.stop()
    --- End diff --
    
    Is there anyway to simplify this?  I'd rather have good unit tests and very simple doc
tests.


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