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https://issues.apache.org/jira/browse/SPARK-15921?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marcelo Vanzin resolved SPARK-15921.
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Resolution: Duplicate
> Spark unable to read partitioned table in avro format and column name in
> upper case
> -----------------------------------------------------------------------------------
>
> Key: SPARK-15921
> URL: https://issues.apache.org/jira/browse/SPARK-15921
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
> Affects Versions: 1.6.0
> Environment: Centos 6.6
> Spark 1.6
> Reporter: Rajkumar Singh
>
> Spark return null value if the field name is uppercase in hive avro
> partitioned table.
> Reproduce:
> {code}
> [root@sandbox ~]# cat file1.csv
> rks,2016
> [root@sandbox ~]# cat file2.csv
> raj,2015
> hive> CREATE TABLE `sample_table`(
> > `name` string)
> > PARTITIONED BY (
> > `year` int)
> > ROW FORMAT DELIMITED
> > FIELDS TERMINATED BY ','
> > STORED AS INPUTFORMAT
> > 'org.apache.hadoop.mapred.TextInputFormat'
> > OUTPUTFORMAT
> > 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
> > LOCATION
> > 'hdfs://sandbox.hortonworks.com:8020/apps/hive/warehouse/sample_table'
> > TBLPROPERTIES (
> > 'transient_lastDdlTime'='1465816403')
> > ;
> load data local inpath '/root/file2.csv' overwrite into table sample_table
> partition(year='2015');
> load data local inpath '/root/file1.csv' overwrite into table sample_table
> partition(year='2016');
> hive> CREATE TABLE sample_table_uppercase
> > PARTITIONeD BY ( YEAR INT)
> > ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.avro.AvroSerDe'
> > STORED AS INPUTFORMAT
> 'org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat'
> > OUTPUTFORMAT
> 'org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat'
> > TBLPROPERTIES (
> > 'avro.schema.literal'='{
> > "namespace": "com.rishav.avro",
> > "name": "student_marks",
> > "type": "record",
> > "fields": [ { "name":"NANME","type":"string"}]
> > }');
> INSERT OVERWRITE TABLE sample_table_uppercase partition(Year) select
> name,year from sample_table;
> hive> select * from sample_table_uppercase;
> OK
> raj 2015
> rks 2016
> now using spark-shell
> scala>val tbl = sqlContext.table("default.sample_table_uppercase");
> scala>tbl.show
> +----+----+
> |name|year|
> +----+----+
> |null|2015|
> |null|2016|
> +----+----+
> {code}
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