leesf commented on code in PR #7235:
URL: https://github.com/apache/hudi/pull/7235#discussion_r1026061223


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rfc/rfc-63/rfc-63.md:
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+
+# RFC-63: Index Function for Optimizing Query Performance
+
+## Proposers
+
+- @yihua
+- @alexeykudinkin
+
+## Approvers
+
+- @vinothchandar
+- @xushiyan
+- @nsivabalan
+
+## Status
+
+JIRA: [HUDI-512](https://issues.apache.org/jira/browse/HUDI-512)
+
+## Abstract
+
+In this RFC, we address the problem of accelerating queries containing 
predicates based on functions defined on a
+column, by introducing **Index Function**, a new indexing capability for 
efficient file pruning.
+
+## Background
+
+To make the queries finish faster, one major optimization technique is to scan 
less data by pruning rows that are not
+needed by the query. This is usually done in two ways:
+
+- **Partition pruning**:  The partition pruning relies on a table with 
physical partitioning, such as Hive partitioning.
+  A partitioned table uses a chosen column such as the date of `timestamp` and 
stores the rows with the same date to the
+  files under the same folder or physical partition, such as 
`date=2022-10-01/`. When the predicate in a query
+  references the partition column of the physical partitioning, the files in 
the partitions not matching the predicate
+  are filtered out, without scanning. For example, for the predicate `date 
between '2022-10-01' and '2022-10-02'`, the
+  partition pruning only returns the files from two partitions, `2022-10-01` 
and `2022-10-02`, for further processing.
+  The granularity of the pruning is at the partition level.
+
+
+- **File pruning**:  The file pruning carries out the pruning of the data at 
the file level, with the help of file-level
+  or record-level index. For example, with column stats index containing 
minimum and maximum values of a column for each
+  file, the files falling out of the range of the values compared to the 
predicate can be pruned. For a predicate
+  with `age < 20`, the file pruning filters out a file with columns stats of 
`[30, 40]` as the minimum and maximum
+  values of the column `age`.
+
+While Apache Hudi already supports partition pruning and file pruning with 
data skipping for different query engines, we
+recognize that the following use cases need better query performance and 
usability:
+
+- File pruning based on functions defined on a column
+- Efficient file pruning for files without physical partitioning
+- Effective file pruning after partition evolution, without rewriting data

Review Comment:
   partition evolution here means change partition column or sth else?



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