[HUDI-1736] failed to read timestamp column in version 0.7.0 even when HIVE_SUPPORT_TIMESTAMP is enabled

• Type: Bug
• Status: Open
• Priority: Major
• Resolution: Unresolved
• Labels: query-eng sev:high sev:triage user-support-issues
• Assignee: Unassigned
• Reporter: sivabalan narayanan
• Created: 29/Mar/21 15:57
• Updated: 13/Dec/21 20:40

Description

sql("select * from employee_rt").show(false)

 

{{174262 [Executor task launch worker for task 12017] ERROR org.apache.spark.executor.Executor - Exception in task 0.0 in stage 31.0 (TID 12017)
java.lang.ClassCastException: org.apache.hadoop.io.LongWritable cannot be cast to org.apache.hadoop.hive.serde2.io.TimestampWritable
at org.apache.hadoop.hive.serde2.objectinspector.primitive.WritableTimestampObjectInspector.getPrimitiveJavaObject(WritableTimestampObjectInspector.java:39)
at org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$14(TableReader.scala:468)
at org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$14$adapted(TableReader.scala:467)
at org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$18(TableReader.scala:493)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)}}

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Steps to reproduce

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import org.apache.spark.sql._
import org.apache.hudi.QuickstartUtils._
import scala.collection.JavaConversions._
import org.apache.spark.sql.SaveMode._
import org.apache.hudi.DataSourceReadOptions._
import org.apache.hudi.DataSourceWriteOptions._
import org.apache.hudi.config.HoodieWriteConfig._
import org.apache.spark.sql.functions._
import org.apache.hudi.QuickstartUtils._
import scala.collection.JavaConversions._
import org.apache.spark.sql.SaveMode._
import org.apache.hudi.DataSourceReadOptions
import org.apache.hudi.DataSourceWriteOptions
import org.apache.hudi.config.HoodieWriteConfig
import org.apache.hudi.hive.MultiPartKeysValueExtractor
import org.apache.spark.sql.functions._
import org.apache.hudi.keygen._
import org.apache.spark.sql.streaming._

case class Person(firstname:String, age:Int, gender:Int)
val personDF = List(Person("tom",45,1), Person("iris",44,0)).toDF.withColumn("ts",unix_timestamp).withColumn("insert_time",current_timestamp)
//val personDF2 = List(Person("peng",56,1), Person("iris",51,0),Person("jacky",25,1)).toDF.withColumn("ts",unix_timestamp).withColumn("insert_time",current_timestamp)

//personDF.write.mode(SaveMode.Overwrite).format("hudi").saveAsTable("employee")

val tableName = "employee"
val hudiCommonOptions = Map(
  "hoodie.compact.inline" -> "true",
  "hoodie.compact.inline.max.delta.commits" ->"5",
  "hoodie.base.path" -> s"/tmp/$tableName",
  "hoodie.table.name" -> tableName,
  "hoodie.datasource.write.table.type"->"MERGE_ON_READ",
  "hoodie.datasource.write.operation" -> "upsert",
  "hoodie.clean.async" -> "true"
)

val hudiHiveOptions = Map(
    DataSourceWriteOptions.HIVE_SYNC_ENABLED_OPT_KEY -> "true",
    DataSourceWriteOptions.HIVE_URL_OPT_KEY -> "jdbc:hive2://localhost:10000",
    DataSourceWriteOptions.HIVE_PARTITION_FIELDS_OPT_KEY -> "gender",
    DataSourceWriteOptions.HIVE_STYLE_PARTITIONING_OPT_KEY -> "true",
    "hoodie.datasource.hive_sync.support_timestamp"->"true",
    DataSourceWriteOptions.HIVE_TABLE_OPT_KEY -> tableName,
    DataSourceWriteOptions.HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY -> classOf[MultiPartKeysValueExtractor].getName
)

val basePath = s"/tmp/$tableName"
personDF.write.format("hudi").
  option(PRECOMBINE_FIELD_OPT_KEY, "ts").
  option(RECORDKEY_FIELD_OPT_KEY, "firstname").
  option(PARTITIONPATH_FIELD_OPT_KEY, "gender").
  options(hudiCommonOptions).
  options(hudiHiveOptions).
  mode(SaveMode.Overwrite).
  save(basePath)

sql("select * from employee_rt").show(false)

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More info: https://github.com/apache/hudi/issues/2544

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