[GitHub] [hudi] vinothchandar commented on a change in pull request #1938: [HUDI-920] Support Incremental query for MOR table

[GitBox <gi...@apache.org>]

vinothchandar commented on a change in pull request #1938:
URL: https://github.com/apache/hudi/pull/1938#discussion_r553482746



##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/utils/HoodieInputFormatUtils.java
##########
@@ -470,4 +471,45 @@ private static HoodieBaseFile refreshFileStatus(Configuration conf, HoodieBaseFi
     }
   }
 
+  /**
+   * List affected file status based on given commits.

Review comment:
       a little bit more clearer doc? does this method obtain all the file status that were affected by the list of commits to check?

##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/utils/HoodieInputFormatUtils.java
##########
@@ -470,4 +471,45 @@ private static HoodieBaseFile refreshFileStatus(Configuration conf, HoodieBaseFi
     }
   }
 
+  /**
+   * List affected file status based on given commits.
+   * @param basePath
+   * @param commitsToCheck
+   * @param timeline
+   * @return HashMap<partitionPath, HashMap<fileName, FileStatus>>
+   * @throws IOException
+   */
+  public static HashMap<String, HashMap<String, FileStatus>> listStatusForAffectedPartitions(
+      Path basePath, List<HoodieInstant> commitsToCheck, HoodieTimeline timeline) throws IOException {
+    // Extract files touched by these commits.
+    // TODO This might need to be done in parallel like listStatus parallelism ?

Review comment:
       Can we redo this such that it can use the metadata table for obtaining the listing? You can see how this is done in HoodieParquetInputFormat. 

##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/utils/HoodieInputFormatUtils.java
##########
@@ -470,4 +471,45 @@ private static HoodieBaseFile refreshFileStatus(Configuration conf, HoodieBaseFi
     }
   }
 
+  /**
+   * List affected file status based on given commits.
+   * @param basePath
+   * @param commitsToCheck
+   * @param timeline
+   * @return HashMap<partitionPath, HashMap<fileName, FileStatus>>
+   * @throws IOException
+   */
+  public static HashMap<String, HashMap<String, FileStatus>> listStatusForAffectedPartitions(
+      Path basePath, List<HoodieInstant> commitsToCheck, HoodieTimeline timeline) throws IOException {
+    // Extract files touched by these commits.
+    // TODO This might need to be done in parallel like listStatus parallelism ?
+    HashMap<String, HashMap<String, FileStatus>> partitionToFileStatusesMap = new HashMap<>();
+    for (HoodieInstant commit: commitsToCheck) {
+      HoodieCommitMetadata commitMetadata = HoodieCommitMetadata.fromBytes(timeline.getInstantDetails(commit).get(),
+          HoodieCommitMetadata.class);
+      for (Map.Entry<String, List<HoodieWriteStat>> entry: commitMetadata.getPartitionToWriteStats().entrySet()) {
+        if (!partitionToFileStatusesMap.containsKey(entry.getKey())) {
+          partitionToFileStatusesMap.put(entry.getKey(), new HashMap<>());
+        }
+        for (HoodieWriteStat stat : entry.getValue()) {
+          String relativeFilePath = stat.getPath();
+          Path fullPath = relativeFilePath != null ? FSUtils.getPartitionPath(basePath, relativeFilePath) : null;
+          if (fullPath != null) {
+            if (partitionToFileStatusesMap.get(entry.getKey()).containsKey(fullPath.getName())) {
+              // If filesystem support Append. Update the FileStatus of log file if being appended.

Review comment:
       you can just pick the latest such file now. it will have the latest log size using `getFileSizeInBytes()`. No need to do the addition here. 

##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/MergeOnReadIncrementalRelation.scala
##########
@@ -0,0 +1,218 @@
+/*
+ * 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.hudi
+
+import org.apache.hadoop.fs.{FileStatus, FileSystem, GlobPattern, Path}
+import org.apache.hadoop.mapred.JobConf
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.model.HoodieRecord
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.listStatusForAffectedPartitions
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+import org.apache.log4j.LogManager
+import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.sources._
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.{Row, SQLContext}
+
+import scala.collection.JavaConversions._
+import scala.collection.mutable.ListBuffer
+
+/**
+  * Experimental.
+  * Relation, that implements the Hoodie incremental view for Merge On Read table.
+  *
+  */
+class MergeOnReadIncrementalRelation(val sqlContext: SQLContext,

Review comment:
       can we subclass `IncrementalRelation` and reuse some of the code esp lines 54-66 etc? worth it?

##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/utils/HoodieInputFormatUtils.java
##########
@@ -470,4 +471,45 @@ private static HoodieBaseFile refreshFileStatus(Configuration conf, HoodieBaseFi
     }
   }
 
+  /**
+   * List affected file status based on given commits.
+   * @param basePath
+   * @param commitsToCheck
+   * @param timeline
+   * @return HashMap<partitionPath, HashMap<fileName, FileStatus>>
+   * @throws IOException
+   */
+  public static HashMap<String, HashMap<String, FileStatus>> listStatusForAffectedPartitions(

Review comment:
       can we just have this in `hudi-spark` for now. thats the only module that needs to call this. 

##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/MergeOnReadIncrementalRelation.scala
##########
@@ -0,0 +1,218 @@
+/*
+ * 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.hudi
+
+import org.apache.hadoop.fs.{FileStatus, FileSystem, GlobPattern, Path}
+import org.apache.hadoop.mapred.JobConf
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.model.HoodieRecord
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.listStatusForAffectedPartitions
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+import org.apache.log4j.LogManager
+import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.sources._
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.{Row, SQLContext}
+
+import scala.collection.JavaConversions._
+import scala.collection.mutable.ListBuffer
+
+/**
+  * Experimental.
+  * Relation, that implements the Hoodie incremental view for Merge On Read table.
+  *
+  */
+class MergeOnReadIncrementalRelation(val sqlContext: SQLContext,
+                                     val optParams: Map[String, String],
+                                     val userSchema: StructType,
+                                     val metaClient: HoodieTableMetaClient)
+  extends BaseRelation with PrunedFilteredScan {
+
+  private val log = LogManager.getLogger(classOf[MergeOnReadIncrementalRelation])
+  private val conf = sqlContext.sparkContext.hadoopConfiguration
+  private val jobConf = new JobConf(conf)
+  private val fs = FSUtils.getFs(metaClient.getBasePath, conf)
+  private val commitTimeline = metaClient.getCommitsAndCompactionTimeline.filterCompletedInstants()
+  if (commitTimeline.empty()) {
+    throw new HoodieException("No instants to incrementally pull")
+  }
+  if (!optParams.contains(DataSourceReadOptions.BEGIN_INSTANTTIME_OPT_KEY)) {
+    throw new HoodieException(s"Specify the begin instant time to pull from using " +
+      s"option ${DataSourceReadOptions.BEGIN_INSTANTTIME_OPT_KEY}")
+  }
+
+  private val lastInstant = commitTimeline.lastInstant().get()
+  private val mergeType = optParams.getOrElse(
+    DataSourceReadOptions.REALTIME_MERGE_OPT_KEY,
+    DataSourceReadOptions.DEFAULT_REALTIME_MERGE_OPT_VAL)
+
+  private val commitsTimelineToReturn = commitTimeline.findInstantsInRange(
+    optParams(DataSourceReadOptions.BEGIN_INSTANTTIME_OPT_KEY),
+    optParams.getOrElse(DataSourceReadOptions.END_INSTANTTIME_OPT_KEY, lastInstant.getTimestamp))
+  log.debug(s"${commitsTimelineToReturn.getInstants.iterator().toList.map(f => f.toString).mkString(",")}")
+  private val commitsToReturn = commitsTimelineToReturn.getInstants.iterator().toList
+  private val schemaUtil = new TableSchemaResolver(metaClient)
+  private val tableAvroSchema = schemaUtil.getTableAvroSchema
+  private val tableStructSchema = AvroConversionUtils.convertAvroSchemaToStructType(tableAvroSchema)
+  private val maxCompactionMemoryInBytes = getMaxCompactionMemoryInBytes(jobConf)
+  private val fileIndex = buildFileIndex()
+
+  override def schema: StructType = tableStructSchema
+
+  override def needConversion: Boolean = false
+
+  override def unhandledFilters(filters: Array[Filter]): Array[Filter] = {
+    val isNotNullFilter = IsNotNull(HoodieRecord.COMMIT_TIME_METADATA_FIELD)
+    val largerThanFilter = GreaterThanOrEqual(HoodieRecord.COMMIT_TIME_METADATA_FIELD, commitsToReturn.head.getTimestamp)
+    val lessThanFilter = LessThanOrEqual(HoodieRecord.COMMIT_TIME_METADATA_FIELD, commitsToReturn.last.getTimestamp)
+    filters :+isNotNullFilter :+ largerThanFilter :+ lessThanFilter
+  }
+
+  override def buildScan(requiredColumns: Array[String], filters: Array[Filter]): RDD[Row] = {
+    log.debug(s"buildScan requiredColumns = ${requiredColumns.mkString(",")}")
+    log.debug(s"buildScan filters = ${filters.mkString(",")}")
+    // config to ensure the push down filter for parquet will be applied.
+    sqlContext.sparkSession.sessionState.conf.setConfString("spark.sql.parquet.filterPushdown", "true")
+    sqlContext.sparkSession.sessionState.conf.setConfString("spark.sql.parquet.recordLevelFilter.enabled", "true")
+    sqlContext.sparkSession.sessionState.conf.setConfString("spark.sql.parquet.enableVectorizedReader", "false")
+    val pushDownFilter = {

Review comment:
       this is the secret sauce to do the filtering at the record level, I guess




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