[CARBONDATA-2979] select count fails when carbondata file is written through SDK and read through sparkfileformat for complex datatype map(struct->array->map) #2774
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… SDK and external table using carbon file format is used to query the data
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Build Success with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder2.1/607/ |
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Build Success with Spark 2.3.1, Please check CI http://136.243.101.176:8080/job/carbondataprbuilder2.3/8868/ |
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Build Success with Spark 2.2.1, Please check CI http://95.216.28.178:8080/job/ApacheCarbonPRBuilder1/799/ |
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LGTM |
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retest this please |
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Build Success with Spark 2.1.0, Please check CI http://136.243.101.176:8080/job/ApacheCarbonPRBuilder2.1/674/ |
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Build Success with Spark 2.2.1, Please check CI http://95.216.28.178:8080/job/ApacheCarbonPRBuilder1/870/ |
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Build Success with Spark 2.3.1, Please check CI http://136.243.101.176:8080/job/carbondataprbuilder2.3/8938/ |
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LGTM |
xuchuanyin
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Oct 19, 2018
…through SDK and read through sparkfileformat for complex datatype map(struct->array->map) Problem Select query failed issue for map type when data is loaded using avro SDK and external table using carbon file format is used to query the data Analysis When data is loaded through Avro SDK which has a schema of type struct<array>, fieldName was hard coded to val because of which during query the schema written in the file footer and schema inferred for the external table had a mismatch which lead to failure. Solution Instead of hard coding the field value as val use the given field name in the schema This closes apache#2774
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Problem
Select query failed issue for map type when data is loaded using avro SDK and external table using carbon file format is used to query the data
Analysis
When data is loaded through Avro SDK which has a schema of type struct<array>, fieldName was hard coded to "val" because of which during query the schema written in the file footer and schema inferred for the external table had a mismatch which lead to failure.
Solution
Instead of hard coding the field value as "val" use the given field name in the schema
No
No
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UT Added
NA