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/*
* 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.hudi

object DeDupeType extends Enumeration {

type dedupeType = Value

val INSERT_TYPE = Value("insert_type")
val UPDATE_TYPE = Value("update_type")
val UPSERT_TYPE = Value("upsert_type")
}
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/*
* 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.hudi

import org.apache.hadoop.fs.{FileSystem, FileUtil, Path}
import org.apache.hudi.common.fs.FSUtils
import org.apache.hudi.common.model.{HoodieBaseFile, HoodieRecord}
import org.apache.hudi.common.table.HoodieTableMetaClient
import org.apache.hudi.common.table.view.HoodieTableFileSystemView
import org.apache.hudi.exception.HoodieException
import org.apache.log4j.Logger
import org.apache.spark.sql.{DataFrame, Row, SQLContext}

import java.util.stream.Collectors
import scala.collection.JavaConversions._
import scala.collection.mutable.{Buffer, HashMap, HashSet, ListBuffer}

/**
* Spark job to de-duplicate data present in a partition path
*/
class DedupeSparkJob(basePath: String,
duplicatedPartitionPath: String,
repairOutputPath: String,
sqlContext: SQLContext,
fs: FileSystem,
dedupeType: DeDupeType.Value) {

val sparkHelper = new SparkHelper(sqlContext, fs)
val LOG = Logger.getLogger(this.getClass)

/**
*
* @param tblName
* @return
*/
def getDupeKeyDF(tblName: String): DataFrame = {
val dupeSql =
s"""
select `${HoodieRecord.RECORD_KEY_METADATA_FIELD}` as dupe_key,
count(*) as dupe_cnt
from ${tblName}
group by `${HoodieRecord.RECORD_KEY_METADATA_FIELD}`
having dupe_cnt > 1
"""
sqlContext.sql(dupeSql)
}

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Done

/**
*
* Check a given partition for duplicates and suggest the deletions that need to be done in each file,
* in order to set things right.
*
* @return
*/
private def planDuplicateFix(): HashMap[String, HashSet[String]] = {
val tmpTableName = s"htbl_${System.currentTimeMillis()}"
val dedupeTblName = s"${tmpTableName}_dupeKeys"

val metadata = HoodieTableMetaClient.builder().setConf(fs.getConf).setBasePath(basePath).build()

val allFiles = fs.listStatus(new org.apache.hadoop.fs.Path(s"$basePath/$duplicatedPartitionPath"))
val fsView = new HoodieTableFileSystemView(metadata, metadata.getActiveTimeline.getCommitTimeline.filterCompletedInstants(), allFiles)
val latestFiles: java.util.List[HoodieBaseFile] = fsView.getLatestBaseFiles().collect(Collectors.toList[HoodieBaseFile]())
val filteredStatuses = latestFiles.map(f => f.getPath)
LOG.info(s" List of files under partition: ${} => ${filteredStatuses.mkString(" ")}")

val df = sqlContext.parquetFile(filteredStatuses: _*)
df.registerTempTable(tmpTableName)
val dupeKeyDF = getDupeKeyDF(tmpTableName)
dupeKeyDF.registerTempTable(dedupeTblName)

// Obtain necessary satellite information for duplicate rows
val dupeDataSql =
s"""
SELECT `_hoodie_record_key`, `_hoodie_partition_path`, `_hoodie_file_name`, `_hoodie_commit_time`
FROM $tmpTableName h
JOIN $dedupeTblName d
ON h.`_hoodie_record_key` = d.dupe_key
"""
val dupeMap = sqlContext.sql(dupeDataSql).collectAsList().groupBy(r => r.getString(0))
getDedupePlan(dupeMap)
}

private def getDedupePlan(dupeMap: Map[String, Buffer[Row]]): HashMap[String, HashSet[String]] = {
val fileToDeleteKeyMap = new HashMap[String, HashSet[String]]()
dupeMap.foreach(rt => {
val (key, rows) = rt

dedupeType match {
case DeDupeType.UPDATE_TYPE =>
/*
This corresponds to the case where all duplicates have been updated at least once.
Once updated, duplicates are bound to have same commit time unless forcefully modified.
*/
rows.init.foreach(r => {
val f = r(2).asInstanceOf[String].split("_")(0)
if (!fileToDeleteKeyMap.contains(f)) {
fileToDeleteKeyMap(f) = HashSet[String]()
}
fileToDeleteKeyMap(f).add(key)
})

case DeDupeType.INSERT_TYPE =>
/*
This corresponds to the case where duplicates got created due to INSERT and have never been updated.
*/
var maxCommit = -1L

rows.foreach(r => {
val c = r(3).asInstanceOf[String].toLong
if (c > maxCommit)
maxCommit = c
})

rows.foreach(r => {
val c = r(3).asInstanceOf[String].toLong
if (c != maxCommit) {
val f = r(2).asInstanceOf[String].split("_")(0)
if (!fileToDeleteKeyMap.contains(f)) {
fileToDeleteKeyMap(f) = HashSet[String]()
}
fileToDeleteKeyMap(f).add(key)
}
})

case DeDupeType.UPSERT_TYPE =>
/*
This corresponds to the case where duplicates got created as a result of inserts as well as updates,
i.e few duplicate records have been updated, while others were never updated.
*/
var maxCommit = -1L

rows.foreach(r => {
val c = r(3).asInstanceOf[String].toLong
if (c > maxCommit)
maxCommit = c
})
val rowsWithMaxCommit = new ListBuffer[Row]()
rows.foreach(r => {
val c = r(3).asInstanceOf[String].toLong
if (c != maxCommit) {
val f = r(2).asInstanceOf[String].split("_")(0)
if (!fileToDeleteKeyMap.contains(f)) {
fileToDeleteKeyMap(f) = HashSet[String]()
}
fileToDeleteKeyMap(f).add(key)
} else {
rowsWithMaxCommit += r
}
})

rowsWithMaxCommit.toList.init.foreach(r => {
val f = r(2).asInstanceOf[String].split("_")(0)
if (!fileToDeleteKeyMap.contains(f)) {
fileToDeleteKeyMap(f) = HashSet[String]()
}
fileToDeleteKeyMap(f).add(key)
})

case _ => throw new IllegalArgumentException("Please provide valid type for deduping!")
}
})
LOG.debug(s"fileToDeleteKeyMap size: ${fileToDeleteKeyMap.size}, map: $fileToDeleteKeyMap")
fileToDeleteKeyMap
}

def fixDuplicates(dryRun: Boolean = true) = {
val metadata = HoodieTableMetaClient.builder().setConf(fs.getConf).setBasePath(basePath).build()

val allFiles = fs.listStatus(new Path(s"$basePath/$duplicatedPartitionPath"))
val fsView = new HoodieTableFileSystemView(metadata, metadata.getActiveTimeline.getCommitTimeline.filterCompletedInstants(), allFiles)

val latestFiles: java.util.List[HoodieBaseFile] = fsView.getLatestBaseFiles().collect(Collectors.toList[HoodieBaseFile]())

val fileNameToPathMap = latestFiles.map(f => (f.getFileId, new Path(f.getPath))).toMap
val dupeFixPlan = planDuplicateFix()

// 1. Copy all latest files into the temp fix path
fileNameToPathMap.foreach { case (fileName, filePath) =>
val badSuffix = if (dupeFixPlan.contains(fileName)) ".bad" else ""
val dstPath = new Path(s"$repairOutputPath/${filePath.getName}$badSuffix")
LOG.info(s"Copying from $filePath to $dstPath")
FileUtil.copy(fs, filePath, fs, dstPath, false, true, fs.getConf)
}

// 2. Remove duplicates from the bad files
dupeFixPlan.foreach { case (fileName, keysToSkip) =>
val instantTime = FSUtils.getCommitTime(fileNameToPathMap(fileName).getName)
val badFilePath = new Path(s"$repairOutputPath/${fileNameToPathMap(fileName).getName}.bad")
val newFilePath = new Path(s"$repairOutputPath/${fileNameToPathMap(fileName).getName}")
LOG.info(" Skipping and writing new file for : " + fileName)
SparkHelpers.skipKeysAndWriteNewFile(instantTime, fs, badFilePath, newFilePath, dupeFixPlan(fileName))
fs.delete(badFilePath, true)
}

// 3. Check that there are no duplicates anymore.
val df = sqlContext.read.parquet(s"$repairOutputPath/*.parquet")
df.registerTempTable("fixedTbl")
val dupeKeyDF = getDupeKeyDF("fixedTbl")
val dupeCnt = dupeKeyDF.count()
if (dupeCnt != 0) {
dupeKeyDF.show()
throw new HoodieException("Still found some duplicates!!.. Inspect output")
}

// 4. Additionally ensure no record keys are left behind.
val sourceDF = sparkHelper.getDistinctKeyDF(fileNameToPathMap.map(t => t._2.toString).toList)
val fixedDF = sparkHelper.getDistinctKeyDF(fileNameToPathMap.map(t => s"$repairOutputPath/${t._2.getName}").toList)
val missedRecordKeysDF = sourceDF.except(fixedDF)
val missedCnt = missedRecordKeysDF.count()
if (missedCnt != 0) {
missedRecordKeysDF.show()
throw new HoodieException("Some records in source are not found in fixed files. Inspect output!!")
}

println("No duplicates found & counts are in check!!!! ")
// 5. Prepare to copy the fixed files back.
fileNameToPathMap.foreach { case (_, filePath) =>
val srcPath = new Path(s"$repairOutputPath/${filePath.getName}")
val dstPath = new Path(s"$basePath/$duplicatedPartitionPath/${filePath.getName}")
if (dryRun) {
LOG.info(s"[JUST KIDDING!!!] Copying from $srcPath to $dstPath")
} else {
// for real
LOG.info(s"[FOR REAL!!!] Copying from $srcPath to $dstPath")
FileUtil.copy(fs, srcPath, fs, dstPath, false, true, fs.getConf)
}
}
}
}
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