@mathieu ОК. Ты прав. Это могло бы быть поддержано, это не дизайн. Обратите внимание, что Spark 2.3 поставляется с другим потоковым движком (который может изменить кеширование).
SparkSession
.builder
.master("local[*]")
.config("spark.sql.warehouse.dir", "C:/tmp/spark")
.config("spark.sql.streaming.checkpointLocation", "C:/tmp/spark/spark-checkpoint")
.appName("my-test")
.getOrCreate
.readStream
.schema(schema)
.json("src/test/data")
.cache
.writeStream
.start
.awaitTermination
ыполнении этого образца в Spark 2.1.0 я получил ошибку. Без.cache вариант это работало как задумано, но с.cache вариант, который я получил:
Exception in thread "main" org.apache.spark.sql.AnalysisException: Queries with streaming sources must be executed with writeStream.start();;
FileSource[src/test/data]
at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$.org$apache$spark$sql$catalyst$analysis$UnsupportedOperationChecker$throwError(UnsupportedOperationChecker.scala:196)
at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:35)
at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:33)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:128)
at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$.checkForBatch(UnsupportedOperationChecker.scala:33)
at org.apache.spark.sql.execution.QueryExecution.assertSupported(QueryExecution.scala:58)
at org.apache.spark.sql.execution.QueryExecution.withCachedData$lzycompute(QueryExecution.scala:69)
at org.apache.spark.sql.execution.QueryExecution.withCachedData(QueryExecution.scala:67)
at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:73)
at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:73)
at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:79)
at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:75)
at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:84)
at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:84)
at org.apache.spark.sql.execution.CacheManager$anonfun$cacheQuery$1.apply(CacheManager.scala:102)
at org.apache.spark.sql.execution.CacheManager.writeLock(CacheManager.scala:65)
at org.apache.spark.sql.execution.CacheManager.cacheQuery(CacheManager.scala:89)
at org.apache.spark.sql.Dataset.persist(Dataset.scala:2479)
at org.apache.spark.sql.Dataset.cache(Dataset.scala:2489)
at org.me.App$.main(App.scala:23)
at org.me.App.main(App.scala)
Любая идея?