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     new 490547e  [HIVEMALL-247][DOC] Recommend 
hive.optimize.cte.materialize.threshold=2 in Hive tuning tips
490547e is described below

commit 490547ea48070949c8df2b0646d1056b7a2acbf0
Author: Makoto Yui <m...@apache.org>
AuthorDate: Fri Apr 12 16:02:17 2019 +0900

    [HIVEMALL-247][DOC] Recommend hive.optimize.cte.materialize.threshold=2 in 
Hive tuning tips
    
    ## What changes were proposed in this pull request?
    
    Recommend `hive.optimize.cte.materialize.threshold=2` in Hive tuning tips
    
    ## What type of PR is it?
    
    Documentation
    
    ## What is the Jira issue?
    
    https://issues.apache.org/jira/browse/HIVEMALL-247
    
    Author: Makoto Yui <m...@apache.org>
    
    Closes #188 from myui/HIVEMALL-247.
---
 docs/gitbook/tips/hadoop_tuning.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/docs/gitbook/tips/hadoop_tuning.md 
b/docs/gitbook/tips/hadoop_tuning.md
index 167a068..77d278f 100644
--- a/docs/gitbook/tips/hadoop_tuning.md
+++ b/docs/gitbook/tips/hadoop_tuning.md
@@ -83,6 +83,10 @@ feature_dimensions (assume here 2^25) * 2 bytes (short) * 2 
(iff covariance is c
 
 Note: Hivemall uses a [sparse 
representation](https://github.com/apache/incubator-hivemall/blob/master/core/src/main/java/hivemall/model/SparseModel.java)
 of prediction model (using a hash table) by the default. Use 
"[-densemodel](https://github.com/apache/incubator-hivemall/blob/master/core/src/main/java/hivemall/LearnerBaseUDTF.java#L87)"
 option to use a dense model.
 
+# Enable CTE materialization
+
+[Hive 2.1.0 or later](https://issues.apache.org/jira/browse/HIVE-11752) 
support CTE materialization through `hive.optimize.cte.materialize.threshold` 
option and it's recommended to `set hive.optimize.cte.materialize.threshold=2` 
when using Hivemall.
+
 # Execution Engine of Hive
 
 We recommend to use Apache Tez for execute engine of Hive for Hivemall queries.

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