qingyuan18 opened a new issue #1854:
URL: https://github.com/apache/hudi/issues/1854
version using
JDK: Jdk 1.8.0_242
Scala: 2.11.12
Spark: 2.4.0
Hudi Spark bundle: 0.5.2-incubating
Steps to reproduce the behavior:
1. create managed hive table
2. using Spark datasource to upset record into it
def upsert(albumDf: DataFrame, tableName: String, key: String, combineKey:
String, tablePath:String):Unit = {
albumDf.write
.format("hudi")
.option(DataSourceWriteOptions.TABLE_TYPE_OPT_KEY,
DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL)
.option(DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY, key)
.option(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY, combineKey)
.option(HoodieWriteConfig.TABLE_NAME, tableName)
.option(DataSourceWriteOptions.OPERATION_OPT_KEY,
DataSourceWriteOptions.UPSERT_OPERATION_OPT_VAL)
.option("hoodie.upsert.shuffle.parallelism", "2")
.mode(SaveMode.Append)
.save(tablePath)
}
3. using spark sql to read the result
val spark: SparkSession = SparkSession.builder()
.appName("hudi-test")
.master("yarn")
.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.config("spark.sql.hive.convertMetastoreParquet", "false") // Uses Hive
SerDe, this is mandatory for MoR tables
.getOrCreate()
spark.sql("select * from xxxx.xxxx_acidtest2 ").show()
submit command: spark-submit --master yarn --conf
spark.sql.hive.convertMetastoreParquet=false
HudiTechSpike-jar-with-dependencies.jar
errors:
java.io.IOException: Not a file:
hdfs://nameservice1/data/operations/racoe/epi/hive/raw/xxxx_acidtest2/default
at
org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:329)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:205)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
seems like it does not recognize the hudi data format/path structure
* Running on Docker? : No
**Additional context**: using spark-shell is the same error
spark-shell --master yarn --conf
spark.sql.hive.convertMetastoreParquet=false --jars
hudi-spark-bundle_2.11-0.5.3.jar
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