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Posted to issues@spark.apache.org by "Chetan Dalal (JIRA)" <ji...@apache.org> on 2015/07/28 21:18:04 UTC

[jira] [Created] (SPARK-9414) HiveContext:saveAsTable creates wrong partition for existing hive table(append mode)

Chetan Dalal created SPARK-9414:
-----------------------------------

             Summary: HiveContext:saveAsTable creates wrong partition for existing hive table(append mode)
                 Key: SPARK-9414
                 URL: https://issues.apache.org/jira/browse/SPARK-9414
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 1.4.0
         Environment: Hadoop 2.6, Spark 1.4.0, Hive 0.14.0.
            Reporter: Chetan Dalal
            Priority: Critical


Raising this bug because I found this issue was ready reported on Apache mail archive and I am facing a similar issue.

-----------original------------------------------
I am using spark 1.4 and HiveContext to append data into a partitioned
hive table. I found that the data insert into the table is correct, but the
partition(folder) created is totally wrong.


 val schemaString = "zone z year month date hh x y height u v w ph phb 
p pb qvapor qgraup qnice qnrain tke_pbl el_pbl"
    val schema =
      StructType(
        schemaString.split(" ").map(fieldName =>
          if (fieldName.equals("zone") || fieldName.equals("z") ||
fieldName.equals("year") || fieldName.equals("month") ||
              fieldName.equals("date") || fieldName.equals("hh") ||
fieldName.equals("x") || fieldName.equals("y"))
            StructField(fieldName, IntegerType, true)
          else
            StructField(fieldName, FloatType, true)
        ))

val pairVarRDD =
sc.parallelize(Seq((Row(2,42,2009,3,1,0,218,365,9989.497.floatValue(),29.627113.floatValue(),19.071793.floatValue(),0.11982734.floatValue(),3174.6812.floatValue(),

97735.2.floatValue(),16.389032.floatValue(),-96.62891.floatValue(),25135.365.floatValue(),2.6476808E-5.floatValue(),0.0.floatValue(),13195.351.floatValue(),

        0.0.floatValue(),0.1.floatValue(),0.0.floatValue()))
    ))

val partitionedTestDF2 = sqlContext.createDataFrame(pairVarRDD, schema)

partitionedTestDF2.write.format("org.apache.spark.sql.hive.orc.DefaultSource")

.mode(org.apache.spark.sql.SaveMode.Append).partitionBy("zone","z","year","month").saveAsTable("test4DimBySpark")

---------------------------------------------------------------------------------------------
The table contains 23 columns (longer than Tuple maximum length), so I
use Row Object to store raw data, not Tuple.
Here is some message from spark when it saved data>>
>>>>
15/06/16 10:39:22 INFO metadata.Hive: Renaming
src:hdfs://service-10-0.local:8020/tmp/hive-patcharee/hive_2015-06-16_10-39-21_205_8768669104487548472-1/-ext-10000/zone=13195/z=0/year=0/month=0/part-00001;dest:
hdfs://service-10-0.local:8020/apps/hive/warehouse/test4dimBySpark/zone=13195/z=0/year=0/month=0/part-00001;Status:true
>>>>
15/06/16 10:39:22 INFO metadata.Hive: New loading path =
hdfs://service-10-0.local:8020/tmp/hive-patcharee/hive_2015-06-16_10-39-21_205_8768669104487548472-1/-ext-10000/zone=13195/z=0/year=0/month=0
with partSpec {zone=13195, z=0, year=0, month=0}
>>>>
>From the raw data (pairVarRDD) zone = 2, z = 42, year = 2009, month =
3. But spark created a partition {zone=13195, z=0, year=0, month=0}. (x)
>>>>
When I queried from hive>>
>>>>
hive> select * from test4dimBySpark;
OK
2    42    2009    3    1.0    0.0    218.0    365.0    9989.497
29.627113    19.071793    0.11982734    -3174.6812    97735.2 16.389032
-96.62891    25135.365    2.6476808E-5    0.0 13195    0    0    0
hive> select zone, z, year, month from test4dimBySpark;
OK
13195    0    0    0
hive> dfs -ls /apps/hive/warehouse/test4dimBySpark/*/*/*/*;
Found 2 items
-rw-r--r--   3 patcharee hdfs       1411 2015-06-16 10:39
/apps/hive/warehouse/test4dimBySpark/zone=13195/z=0/year=0/month=0/part-00001
>>>>
The data stored in the table is correct zone = 2, z = 42, year = 2009,
month = 3, but the partition created was wrong
"zone=13195/z=0/year=0/month=0" (x)






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