chaoqin-li1123 commented on code in PR #46139: URL: https://github.com/apache/spark/pull/46139#discussion_r1590520510
########## python/docs/source/user_guide/sql/python_data_source.rst: ########## @@ -84,6 +93,131 @@ Define the reader logic to generate synthetic data. Use the `faker` library to p row.append(value) yield tuple(row) +**Implement the Stream Reader** + +.. code-block:: python + + class RangePartition(InputPartition): + def __init__(self, start, end): + self.start = start + self.end = end + + class FakeStreamReader(DataSourceStreamReader): + def __init__(self, schema, options): + self.current = 0 + + def initialOffset(self): + return {"offset": 0} + + def latestOffset(self): + self.current += 2 + return {"offset": self.current} + + def partitions(self, start, end): + return [RangePartition(start["offset"], end["offset"])] + + def commit(self, end): + pass + + def read(self, partition): + start, end = partition.start, partition.end + for i in range(start, end): + yield (i, str(i)) + +This is a dummy streaming data reader that generate 2 rows in every microbatch. The streamReader instance has a integer offset that increase by 2 in every microbatch. + +:meth:`pyspark.sql.datasource.DataSourceStreamReader.initialOffset` should return the initial start offset of the reader. + +:meth:`pyspark.sql.datasource.DataSourceStreamReader.latestOffset` return the current latest offset that the next microbatch will read to. + +:meth:`pyspark.sql.datasource.DataSourceStreamReader.partitions` plans the partitioning of the current microbatch defined by start and end offset, it needs to return a sequence of :class:`InputPartition` object. + +:meth:`pyspark.sql.datasource.DataSourceStreamReader.read` takes a partition as an input and read an iterator of tuples from the data source. + +:meth:`pyspark.sql.datasource.DataSourceStreamReader.commit` is invoked when the query has finished processing data before end offset, this can be used to clean up resource. Review Comment: Moved to doc string. ########## python/docs/source/user_guide/sql/python_data_source.rst: ########## @@ -84,6 +93,131 @@ Define the reader logic to generate synthetic data. Use the `faker` library to p row.append(value) yield tuple(row) +**Implement the Stream Reader** + +.. code-block:: python + + class RangePartition(InputPartition): + def __init__(self, start, end): + self.start = start + self.end = end + + class FakeStreamReader(DataSourceStreamReader): + def __init__(self, schema, options): + self.current = 0 + + def initialOffset(self): Review Comment: Typing added. ########## python/docs/source/user_guide/sql/python_data_source.rst: ########## @@ -84,6 +93,131 @@ Define the reader logic to generate synthetic data. Use the `faker` library to p row.append(value) yield tuple(row) +**Implement the Stream Reader** + +.. code-block:: python + + class RangePartition(InputPartition): + def __init__(self, start, end): + self.start = start + self.end = end + + class FakeStreamReader(DataSourceStreamReader): + def __init__(self, schema, options): + self.current = 0 + + def initialOffset(self): + return {"offset": 0} + + def latestOffset(self): + self.current += 2 + return {"offset": self.current} + + def partitions(self, start, end): + return [RangePartition(start["offset"], end["offset"])] + + def commit(self, end): + pass + + def read(self, partition): + start, end = partition.start, partition.end + for i in range(start, end): + yield (i, str(i)) + +This is a dummy streaming data reader that generate 2 rows in every microbatch. The streamReader instance has a integer offset that increase by 2 in every microbatch. Review Comment: Moved under header. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org