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The following commit(s) were added to refs/heads/master by this push:
     new 977f64f0904e [SPARK-46357] Replace incorrect documentation use of 
setConf with conf.set
977f64f0904e is described below

commit 977f64f0904e46e72cbe5b2252f2657dde29c90c
Author: Nicholas Chammas <nicholas.cham...@gmail.com>
AuthorDate: Thu Dec 14 11:07:20 2023 +0800

    [SPARK-46357] Replace incorrect documentation use of setConf with conf.set
    
    ### What changes were proposed in this pull request?
    
    `setConf` is a method on `SQLContext`. The docs perhaps used to refer to 
`SQLContext`, but now they refer to `SparkSession`, which does not have this 
method.
    
    This PR updates the docs to use the appropriate method for making 
configuration settings against `SparkSession`.
    
    ### Why are the changes needed?
    
    The current documentation is incorrect.
    
    ### Does this PR introduce _any_ user-facing change?
    
    Yes.
    
    ### How was this patch tested?
    
    No testing.
    
    ### Was this patch authored or co-authored using generative AI tooling?
    
    No.
    
    Closes #44290 from nchammas/SPARK-46357-setConf-confset.
    
    Authored-by: Nicholas Chammas <nicholas.cham...@gmail.com>
    Signed-off-by: Kent Yao <y...@apache.org>
---
 docs/sql-data-sources-avro.md    | 2 +-
 docs/sql-data-sources-parquet.md | 2 +-
 docs/sql-performance-tuning.md   | 4 ++--
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/sql-data-sources-avro.md b/docs/sql-data-sources-avro.md
index 82f876eae2c5..898afe9de87f 100644
--- a/docs/sql-data-sources-avro.md
+++ b/docs/sql-data-sources-avro.md
@@ -330,7 +330,7 @@ Data source options of Avro can be set via:
   </tr></table>
 
 ## Configuration
-Configuration of Avro can be done using the `setConf` method on SparkSession 
or by running `SET key=value` commands using SQL.
+Configuration of Avro can be done via `spark.conf.set` or by running `SET 
key=value` commands using SQL.
 <table>
   <thead><tr><th><b>Property 
Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Since 
Version</b></th></tr></thead>
   <tr>
diff --git a/docs/sql-data-sources-parquet.md b/docs/sql-data-sources-parquet.md
index 20f6d556cdf7..7d8034321481 100644
--- a/docs/sql-data-sources-parquet.md
+++ b/docs/sql-data-sources-parquet.md
@@ -431,7 +431,7 @@ Other generic options can be found in <a 
href="https://spark.apache.org/docs/lat
 
 ### Configuration
 
-Configuration of Parquet can be done using the `setConf` method on 
`SparkSession` or by running
+Configuration of Parquet can be done via `spark.conf.set` or by running
 `SET key=value` commands using SQL.
 
 <table>
diff --git a/docs/sql-performance-tuning.md b/docs/sql-performance-tuning.md
index 2dec65cc553e..4ede18d1938b 100644
--- a/docs/sql-performance-tuning.md
+++ b/docs/sql-performance-tuning.md
@@ -31,7 +31,7 @@ Spark SQL can cache tables using an in-memory columnar format 
by calling `spark.
 Then Spark SQL will scan only required columns and will automatically tune 
compression to minimize
 memory usage and GC pressure. You can call 
`spark.catalog.uncacheTable("tableName")` or `dataFrame.unpersist()` to remove 
the table from memory.
 
-Configuration of in-memory caching can be done using the `setConf` method on 
`SparkSession` or by running
+Configuration of in-memory caching can be done via `spark.conf.set` or by 
running
 `SET key=value` commands using SQL.
 
 <table>
@@ -297,7 +297,7 @@ This feature coalesces the post shuffle partitions based on 
the map output stati
    </tr>
  </table>
 
-### Spliting skewed shuffle partitions
+### Splitting skewed shuffle partitions
  <table>
    <thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since 
Version</th></tr></thead>
    <tr>


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