viirya commented on a change in pull request #33683: URL: https://github.com/apache/spark/pull/33683#discussion_r689210382
########## File path: docs/structured-streaming-programming-guide.md ########## @@ -1814,6 +1814,82 @@ Specifically for built-in HDFS state store provider, users can check the state s it is best if cache missing count is minimized that means Spark won't waste too much time on loading checkpointed state. User can increase Spark locality waiting configurations to avoid loading state store providers in different executors across batches. +### 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 state store operations crossing +batches. There are two build-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 backed by files in an HDFS-compatible file system. All Review comment: Should we also mention the data is stored in memory map in executors? -- 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