HeartSaVioR commented on code in PR #40937: URL: https://github.com/apache/spark/pull/40937#discussion_r1178532487
########## connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/SparkConnectStreamingQueryCache.scala: ########## @@ -0,0 +1,200 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.connect.service + +import java.util.concurrent.Executors +import java.util.concurrent.ScheduledExecutorService +import java.util.concurrent.TimeUnit +import javax.annotation.concurrent.GuardedBy + +import scala.collection.mutable +import scala.concurrent.duration.Duration +import scala.concurrent.duration.DurationInt +import scala.util.control.NonFatal + +import org.apache.spark.internal.Logging +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.streaming.StreamingQuery +import org.apache.spark.util.Clock +import org.apache.spark.util.SystemClock + +/** + * Caches Spark-Connect streaming query references and the sessions. When a query is stopped (i.e. + * no longer active), it is cached for 1 hour so that it is accessible from the client side. It + * runs a background thread to run a periodic task that does the following: + * - Check the status of the queries, and drops those that expired (1 hour after being stopped). + * - Keep the associated session active by invoking supplied function `sessionKeepAliveFn`. + * + * This class helps with supporting following semantics for streaming query sessions: + * - Keep the session and session mapping at connect server alive as long as a streaming query + * is active. Even if the client side has disconnected. + * - This matches how streaming queries behave in Spark. The queries continue to run if + * notebook or job session is lost. + * - Once a query is stopped, the reference and mappings are maintained for 1 hour and will be + * accessible from the client. This allows time for client to fetch status. + * - During this time if the query is restarted (i.e. has a new run id), the reference to + * previous run is dropped. As a result logical query has only the most recent query + * reference cached. This policy can be revisited to cache multiple runs for a query. + * + * Note that these semantics are evolving and might change before being finalized in Connect. + */ +private[connect] class SparkConnectStreamingQueryCache( + val sessionKeepAliveFn: (String, String) => Unit, // (userId, sessionId) => Unit. + val clock: Clock = new SystemClock(), + private val stoppedQueryCachePeriod: Duration = 1.hour, // Configurable for testing. + private val sessionPollingPeriod: Duration = 1.minute // Configurable for testing. +) extends Logging { + + import SparkConnectStreamingQueryCache._ + + def registerNewStreamingQuery(sessionHolder: SessionHolder, query: StreamingQuery): Unit = { Review Comment: The possible problematic case is that multiple remote sessions are trying to run the streaming query with same checkpoint. Pretty sure it's not something Spark supports and one of the query will eventually survive (others will fail), but at least driver is able to run multiple streaming queries with the same checkpoint concurrently. Please make sure this won't break the key of the cache. Using runId would avoid the problem, but I guess there would be a reason to use query ID instead. -- 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
