Apache Spark reassigned SPARK-23963:

    Assignee:     (was: Apache Spark)

> Queries on text-based Hive tables grow disproportionately slower as the 
> number of columns increase
> --------------------------------------------------------------------------------------------------
>                 Key: SPARK-23963
>                 URL: https://issues.apache.org/jira/browse/SPARK-23963
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Bruce Robbins
>            Priority: Minor
> TableReader gets disproportionately slower as the number of columns in the 
> query increase.
> For example, reading a table with 6000 columns is 4 times more expensive per 
> record than reading a table with 3000 columns, rather than twice as expensive.
> The increase in processing time is due to several Lists (fieldRefs, 
> fieldOrdinals, and unwrappers), each of which the reader accesses by column 
> number for each column in a record. Because each List has O\(n\) time for 
> lookup by column number, these lookups grow increasingly expensive as the 
> column count increases.
> When I patched the code to change those 3 Lists to Arrays, the query times 
> became proportional.

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