/*
 * 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.functional

import scala.collection.JavaConversions._

import org.apache.hudi.common.testutils.HoodieTestDataGenerator
import org.apache.hudi.config.{HoodieIndexConfig, HoodieLayoutConfig, HoodieWriteConfig}
import org.apache.hudi.{DataSourceReadOptions, DataSourceWriteOptions, HoodieDataSourceHelpers}
import org.apache.hudi.common.testutils.RawTripTestPayload.recordsToStrings
import org.apache.hudi.index.HoodieIndex.IndexType
import org.apache.hudi.keygen.constant.KeyGeneratorOptions
import org.apache.hudi.testutils.HoodieClientTestBase

import org.apache.spark.sql._
import org.junit.jupiter.api.{AfterEach, BeforeEach, Test}
import org.junit.jupiter.api.Assertions.{assertEquals, assertTrue}

import org.apache.hudi.table.action.commit.SparkBucketIndexPartitioner
import org.apache.hudi.table.storage.HoodieStorageLayout

/**
 *
 */
class TestDataSourceForBucketIndex extends HoodieClientTestBase {

  var spark: SparkSession = null
  val commonOpts = Map(
    "hoodie.insert.shuffle.parallelism" -> "4",
    "hoodie.upsert.shuffle.parallelism" -> "4",
    "hoodie.bulkinsert.shuffle.parallelism" -> "2",
    DataSourceWriteOptions.RECORDKEY_FIELD.key -> "_row_key",
    DataSourceWriteOptions.PARTITIONPATH_FIELD.key -> "partition",
    DataSourceWriteOptions.PRECOMBINE_FIELD.key -> "timestamp",
    HoodieWriteConfig.TBL_NAME.key -> "hoodie_test",
    HoodieIndexConfig.INDEX_TYPE.key -> IndexType.BUCKET.name,
    HoodieIndexConfig.BUCKET_INDEX_NUM_BUCKETS.key -> "8",
    KeyGeneratorOptions.RECORDKEY_FIELD_NAME.key -> "_row_key",
    HoodieLayoutConfig.LAYOUT_TYPE.key -> HoodieStorageLayout.LayoutType.BUCKET.name,
    HoodieLayoutConfig.LAYOUT_PARTITIONER_CLASS_NAME.key -> classOf[SparkBucketIndexPartitioner[_]].getName
  )

  @BeforeEach override def setUp(): Unit = {
    initPath()
    initSparkContexts()
    spark = sqlContext.sparkSession
    initTestDataGenerator()
    initFileSystem()
  }

  @AfterEach override def tearDown(): Unit = {
    cleanupSparkContexts()
    cleanupTestDataGenerator()
    cleanupFileSystem()
  }

  @Test def testDoubleInsert(): Unit = {
    val records1 = recordsToStrings(dataGen.generateInserts("001", 100)).toList
    val inputDF1: Dataset[Row] = spark.read.json(spark.sparkContext.parallelize(records1, 2))
    inputDF1.write.format("org.apache.hudi")
      .options(commonOpts)
      .option("hoodie.compact.inline", "false") // else fails due to compaction & deltacommit instant times being same
      .option(DataSourceWriteOptions.OPERATION.key, DataSourceWriteOptions.INSERT_OPERATION_OPT_VAL)
      .option(DataSourceWriteOptions.TABLE_TYPE.key, DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL)
      .mode(SaveMode.Append)
      .save(basePath)
    assertTrue(HoodieDataSourceHelpers.hasNewCommits(fs, basePath, "000"))
    val records2 = recordsToStrings(dataGen.generateInserts("002", 100)).toList
    val inputDF2: Dataset[Row] = spark.read.json(spark.sparkContext.parallelize(records2, 2))
    inputDF2.write.format("org.apache.hudi")
      .options(commonOpts)
      .option("hoodie.compact.inline", "false")
      .option(DataSourceWriteOptions.OPERATION.key, DataSourceWriteOptions.INSERT_OPERATION_OPT_VAL)
      .option(DataSourceWriteOptions.TABLE_TYPE.key, DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL)
      .mode(SaveMode.Append)
      .save(basePath)
    val hudiSnapshotDF1 = spark.read.format("org.apache.hudi")
      .option(DataSourceReadOptions.QUERY_TYPE.key, DataSourceReadOptions.QUERY_TYPE_SNAPSHOT_OPT_VAL)
      .load(basePath + "/*/*/*/*")
    assertEquals(200, hudiSnapshotDF1.count())
  }

  @Test def testCountWithBucketIndex(): Unit = {
    // First Operation:
    // Producing parquet files to three default partitions.
    // SNAPSHOT view on MOR table with parquet files only.
    val records1 = recordsToStrings(dataGen.generateInserts("001", 100)).toList
    val inputDF1: Dataset[Row] = spark.read.json(spark.sparkContext.parallelize(records1, 2))
    inputDF1.write.format("org.apache.hudi")
        .options(commonOpts)
        .option("hoodie.compact.inline", "false") // else fails due to compaction & deltacommit instant times being same
        .option(DataSourceWriteOptions.OPERATION.key, DataSourceWriteOptions.INSERT_OVERWRITE_OPERATION_OPT_VAL)
        .option(DataSourceWriteOptions.TABLE_TYPE.key, DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL)
        .mode(SaveMode.Append)
        .save(basePath)
    assertTrue(HoodieDataSourceHelpers.hasNewCommits(fs, basePath, "000"))
    val hudiSnapshotDF1 = spark.read.format("org.apache.hudi")
        .option(DataSourceReadOptions.QUERY_TYPE.key, DataSourceReadOptions.QUERY_TYPE_SNAPSHOT_OPT_VAL)
        .load(basePath + "/*/*/*/*")
    assertEquals(100, hudiSnapshotDF1.count()) // still 100, since we only updated

    // Second Operation:
    // Upsert the update to the default partitions with duplicate records. Produced a log file for each parquet.
    // SNAPSHOT view should read the log files only with the latest commit time.
    val records2 = recordsToStrings(dataGen.generateUniqueUpdates("002", 100)).toList
    val inputDF2: Dataset[Row] = spark.read.json(spark.sparkContext.parallelize(records2, 2))
    inputDF2.write.format("org.apache.hudi")
        .options(commonOpts)
        .mode(SaveMode.Append)
        .save(basePath)
    val hudiSnapshotDF2 = spark.read.format("org.apache.hudi")
        .option(DataSourceReadOptions.QUERY_TYPE.key, DataSourceReadOptions.QUERY_TYPE_SNAPSHOT_OPT_VAL)
        .load(basePath + "/*/*/*/*")
    assertEquals(100, hudiSnapshotDF2.count()) // still 100, since we only updated
    val commit1Time = hudiSnapshotDF1.select("_hoodie_commit_time").head().get(0).toString
    val commit2Time = hudiSnapshotDF2.select("_hoodie_commit_time").head().get(0).toString
    assertEquals(hudiSnapshotDF2.select("_hoodie_commit_time").distinct().count(), 1)
    assertTrue(commit2Time > commit1Time)
    assertEquals(100, hudiSnapshotDF2.join(hudiSnapshotDF1, Seq("_hoodie_record_key"), "left").count())

    val partitionPaths = new Array[String](1)
    partitionPaths.update(0, "2020/01/10")
    val newDataGen = new HoodieTestDataGenerator(partitionPaths)
    val records4 = recordsToStrings(newDataGen.generateInserts("004", 100)).toList
    val inputDF4: Dataset[Row] = spark.read.json(spark.sparkContext.parallelize(records4, 2))
    inputDF4.write.format("org.apache.hudi")
        .options(commonOpts)
        .mode(SaveMode.Append)
        .save(basePath)
    val hudiSnapshotDF4 = spark.read.format("org.apache.hudi")
        .option(DataSourceReadOptions.QUERY_TYPE.key, DataSourceReadOptions.QUERY_TYPE_SNAPSHOT_OPT_VAL)
        .load(basePath + "/*/*/*/*")
    // 200, because we insert 100 records to a new partition
    assertEquals(200, hudiSnapshotDF4.count())
    assertEquals(100,
        hudiSnapshotDF1.join(hudiSnapshotDF4, Seq("_hoodie_record_key"), "inner").count())
  }
}
