Hi all, I have known that ORC provides three level of indexes within each file, file level, stripe level, and row level. The file and stripe level statistics are in the file footer so that they are easy to access to determine if the rest of the file needs to be read at all. Row level indexes include both column statistics for each row group and position for seeking to the start of the row group.
The following is my understanding: 1. The file and stripe level indexes are forcibly generated, we can not control them. 2. The row level indexes can be configured by "orc.create.index"(whether to create row indexes) and "orc.row.index.stride"(number of rows between index entries). 3. Each Index has statistics of min, max for each column, so sort data by the filter column will bring better performance. 4. To use any one of the three level of indexes,we should enable predicate push-down by setting spark.sql.orc.filterPushdown=true (in sparkSQL) or hive.optimize.ppd=true (in hive). But I found the build-in indexes in ORC files did not work both in spark 1.5.2 and hive 1.2.1: First, when the query statement with where clause did't match any record (the filter column had a value beyond the range of data), the performance when enabled predicate push-down was almost the same with when disabled predicate push-down. I think, when the filter column has a value beyond the range of data, all of the orc files will not be scanned if use file level indexes, so the performance should improve obviously. The second, when enabled "orc.create.index" and sorted data by filter column and where clause can only match a few records, the performance when enabled predicate push-down was almost the same with when disabled predicate push-down. The third, when enabled predicate push-down and "orc.create.index", the performance when filter column had a value beyond the range of data was almost the same with when filter column had a value covering almost the whole data. So, has anyone used ORC's build-in indexes before (especially in spark SQL)? What's my issue? Thanks! Joseph
