rdblue commented on a change in pull request #24173: URL: https://github.com/apache/spark/pull/24173#discussion_r528921081
########## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/StateSchemaCompatibilityChecker.scala ########## @@ -0,0 +1,120 @@ +/* + * 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.execution.streaming.state + +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.Path + +import org.apache.spark.internal.Logging +import org.apache.spark.sql.execution.streaming.CheckpointFileManager +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.types.{StructField, StructType} + +case class StateSchemaNotCompatible(message: String) extends Exception(message) + +class StateSchemaCompatibilityChecker( + providerId: StateStoreProviderId, + hadoopConf: Configuration) extends Logging { + + private val storeCpLocation = providerId.storeId.storeCheckpointLocation() + private val fm = CheckpointFileManager.create(storeCpLocation, hadoopConf) + private val schemaFileLocation = schemaFile(storeCpLocation) + + fm.mkdirs(schemaFileLocation.getParent) + + def check(keySchema: StructType, valueSchema: StructType): Unit = { + if (fm.exists(schemaFileLocation)) { + logDebug(s"Schema file for provider $providerId exists. Comparing with provided schema.") + val (storedKeySchema, storedValueSchema) = readSchemaFile() + + def fieldCompatible(fieldOld: StructField, fieldNew: StructField): Boolean = { + // compatibility for nullable + // - same: OK + // - non-nullable -> nullable: OK + // - nullable -> non-nullable: Not compatible + (fieldOld.dataType == fieldNew.dataType) && + ((fieldOld.nullable == fieldNew.nullable) || + (!fieldOld.nullable && fieldNew.nullable)) + } + + def schemaCompatible(schemaOld: StructType, schemaNew: StructType): Boolean = { + (schemaOld.length == schemaNew.length) && + schemaOld.zip(schemaNew).forall { case (f1, f2) => fieldCompatible(f1, f2) } + } + + val errorMsg = "Provided schema doesn't match to the schema for existing state! " + + "Please note that Spark allow difference of field name: check count of fields " + + "and data type of each field.\n" + + s"- provided schema: key $keySchema value $valueSchema\n" + + s"- existing schema: key $storedKeySchema value $storedValueSchema\n" + + s"If you want to force running query without schema validation, please set " + + s"${SQLConf.STATE_SCHEMA_CHECK_ENABLED.key} to false." + + if (storedKeySchema.equals(keySchema) && storedValueSchema.equals(valueSchema)) { + // schema is exactly same + } else if (!schemaCompatible(storedKeySchema, keySchema) || + !schemaCompatible(storedValueSchema, valueSchema)) { + logError(errorMsg) + throw StateSchemaNotCompatible(errorMsg) + } else { + logInfo("Detected schema change which is compatible: will overwrite schema file to new.") + // It tries best-effort to overwrite current schema file. + // the schema validation doesn't break even it fails, though it might miss on detecting + // change which is not a big deal. + createSchemaFile(keySchema, valueSchema) + } + } else { + // schema doesn't exist, create one now + logDebug(s"Schema file for provider $providerId doesn't exist. Creating one.") + createSchemaFile(keySchema, valueSchema) + } + } + + private def readSchemaFile(): (StructType, StructType) = { + val inStream = fm.open(schemaFileLocation) + try { + val keySchemaStr = inStream.readUTF() + val valueSchemaStr = inStream.readUTF() + + (StructType.fromString(keySchemaStr), StructType.fromString(valueSchemaStr)) + } catch { + case e: Throwable => + logError(s"Fail to read schema file from $schemaFileLocation", e) + throw e + } finally { + inStream.close() + } + } + + private def createSchemaFile(keySchema: StructType, valueSchema: StructType): Unit = { + val outStream = fm.createAtomic(schemaFileLocation, overwriteIfPossible = true) + try { + outStream.writeUTF(keySchema.json) Review comment: I think this is a good thing to consider. My initial thought is that we can always use a different file name if this changes and update logic to look for an update. It also doesn't seem like much of this will change, considering it just has the JSON representation of schemas, but I don't think that's a particularly strong argument. ---------------------------------------------------------------- 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. 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
