chaoqin-li1123 commented on code in PR #45023:
URL: https://github.com/apache/spark/pull/45023#discussion_r1501274208
##########
python/pyspark/sql/datasource.py:
##########
@@ -298,6 +320,117 @@ def read(self, partition: InputPartition) ->
Iterator[Union[Tuple, Row]]:
...
+class DataSourceStreamReader(ABC):
+ """
+ A base class for streaming data source readers. Data source stream readers
are responsible
+ for outputting data from a streaming data source.
+
+ .. versionadded: 4.0.0
+ """
+
+ def initialOffset(self) -> dict:
+ """
+ Return the initial offset of the streaming data source.
+ A new streaming query starts reading data from the initial offset.
+ If Spark is restarting an existing query, it will restart from the
check-pointed offset
+ rather than the initial one.
+
+ Returns
+ -------
+ dict
+ A dict whose key and values are str type.
+ """
+ ...
+ raise PySparkNotImplementedError(
+ error_class="NOT_IMPLEMENTED",
+ message_parameters={"feature": "initialOffset"},
+ )
+
+ def latestOffset(self) -> dict:
+ """
+ Returns the most recent offset available.
+
+ Returns
+ -------
+ dict
+ A dict whose key and values are str type.
+ """
+ ...
+ raise PySparkNotImplementedError(
+ error_class="NOT_IMPLEMENTED",
+ message_parameters={"feature": "latestOffset"},
+ )
+
+ def partitions(self, start: dict, end: dict) -> Sequence[InputPartition]:
+ """
+ Returns a list of InputPartition given the start and end offsets.
Each InputPartition
+ represents a data split that can be processed by one Spark task.
+
+ Parameters
+ ----------
+ start : dict
+ The start offset of the microbatch to plan partitioning.
+ end : dict
+ The end offset of the microbatch to plan partitioning.
Review Comment:
We use dict here because we want to enforce the object to be json
serializable.
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