Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/20484#discussion_r165567650
--- Diff: docs/sql-programming-guide.md ---
@@ -1776,6 +1776,77 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
## Upgrading From Spark SQL 2.2 to 2.3
+ - Since Spark 2.3, Spark supports a vectorized ORC reader with a new ORC
file format for ORC files and Hive ORC tables. To do that, the following
configurations are newly added or change their default values.
+
+ <table class="table">
+ <tr>
+ <th>
+ <b>Property Name</b>
+ </th>
+ <th>
+ <b>Default</b>
+ </th>
+ <th>
+ <b>Meaning</b>
+ </th>
+ </tr>
+ <tr>
+ <td>
+ spark.sql.orc.impl
+ </td>
+ <td>
+ native
+ </td>
+ <td>
+ The name of ORC implementation: 'native' means the native
version of ORC support instead of the ORC library in Hive 1.2.1. It is 'hive'
by default prior to Spark 2.3.
--- End diff --
` the native version of ORC support` -> `the native ORC support that is
built on Apache ORC 1.4.1`
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