viirya commented on a change in pull request #33683:
URL: https://github.com/apache/spark/pull/33683#discussion_r689245759
##########
File path: docs/structured-streaming-programming-guide.md
##########
@@ -1792,7 +1792,85 @@ hence the number is not same as the number of original
input rows. You'd like to
There's a known workaround: split your streaming query into multiple queries
per stateful operator, and ensure
end-to-end exactly once per query. Ensuring end-to-end exactly once for the
last query is optional.
-### State Store and task locality
+### State Store
+
+State store is a versioned key-value store which provides both read and write
operations. In
+structured streaming, we use the state store provider to handle the stateful
operations across
+batches. There are two built-in state store provider implementations. End
users can also implement
+their own state store provider by extending StateStoreProvider interface.
+
+#### HDFS state store provider
+
+The HDFS backend state store provider is the default implementation of
[[StateStoreProvider]] and
+[[StateStore]] in which all the data is stated in memory map in the first
stage, and then backed
Review comment:
stated? stored?
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