Spark / Hive - org.apache.hadoop.hive.serde2.io.DoubleWritable cannot be cast to org.apache.hadoop.io.Text

Exception -

java.lang.ClassCastException: org.apache.hadoop.hive.serde2.io.DoubleWritable cannot be cast to org.apache.hadoop.io.Text
 at org.apache.hadoop.hive.serde2.objectinspector.primitive.WritableStringObjectInspector.getPrimitiveWritableObject(WritableStringObjectInspector.java:41)
 at org.apache.spark.sql.hive.HiveInspectors$$anonfun$unwrapperFor$23.apply(HiveInspectors.scala:547)
 at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$14$$anonfun$apply$15.apply(TableReader.scala:426)
 at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$14$$anonfun$apply$15.apply(TableReader.scala:426)
 at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$fillObject$2.apply(TableReader.scala:442)

This exception may be occurring because underlying ORC File has a column with data Type Double, whereas Hive table has column type as String. This error can be rectified by correcting the data type.

Comments

Hive Parse JSON with Array Columns and Explode it in to Multiple rows.

Say we have a JSON String like below - { "billingCountry":"US" "orderItems":[ { "itemId":1, "product":"D1" }, { "itemId":2, "product":"D2" } ] } And, our aim is to get output parsed like below - itemId product 1 D1 2 D2 First, We can parse JSON as follows to get JSON String get_json_object(value, '$.orderItems.itemId') as itemId get_json_object(value, '$.orderItems.product') as product Second, Above will result String value like "[1,2]". We want to convert it to Array as follows - split(regexp_extract(get_json_object(value, '$.orderItems.itemId'),'^\\["(.*)\\"]$',1),'","') as itemId split(regexp_extract(get_json_object(value, '$.orderItems.product'),'^\\["(.*)\\"]$',1),&

org.apache.spark.sql.AnalysisException: Cannot overwrite a path that is also being read from.;

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One may face following error while copying data from one cluster to other, using Distcp Command: hadoop distcp -i {src} {tgt} Error: org.apache.hadoop.toolsCopyListing$DulicateFileException: File would cause duplicates. Ideally there can't be same file names. So, what might be happening in your case is you trying to copy partitioned table from one cluster to other. And, 2 different named partitions have same file name. Your solution is to correct Source path {src} in your command, such that you provide path uptil partitioned sub directory, not the file. For ex - Refer below : /a/partcol=1/file1.txt /a/partcol=2/file1.txt If you use {src} as "/a/*/*" then you will get the error "File would cause duplicates." But, if you use {src} as "/a" then you will not get error in copying.

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