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.
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