This is an automated email from the ASF dual-hosted git repository.
xushiyan pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/hudi.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 79c1733 [MINOR] Fix Spark SQL cases (#4289)
79c1733 is described below
commit 79c17331c88441e556340cc5c60725a553010df6
Author: Raymond Xu <[email protected]>
AuthorDate: Sat Dec 11 11:50:18 2021 -0800
[MINOR] Fix Spark SQL cases (#4289)
---
website/docs/quick-start-guide.md | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/website/docs/quick-start-guide.md
b/website/docs/quick-start-guide.md
index 1aa2801..086b3ef 100644
--- a/website/docs/quick-start-guide.md
+++ b/website/docs/quick-start-guide.md
@@ -15,7 +15,7 @@ After each write operation we will also show how to read the
data both snapshot
## Setup
Hudi works with Spark-2.4.3+ & Spark 3.x versions. You can follow instructions
[here](https://spark.apache.org/downloads) for setting up spark.
-As of 0.9.0 release, spark-sql dml support has been added and is experimental.
+As of 0.9.0 release, Spark SQL DML support has been added and is experimental.
<Tabs
defaultValue="scala"
@@ -48,21 +48,21 @@ spark-shell \
</TabItem>
<TabItem value="sparksql">
-Hudi support using spark sql to write and read data with the
**HoodieSparkSessionExtension** sql extension.
-From the extracted directory run spark-sql with Hudi as:
+Hudi support using Spark SQL to write and read data with the
**HoodieSparkSessionExtension** sql extension.
+From the extracted directory run Spark SQL with Hudi as:
```shell
-# spark sql for spark 3
+# Spark SQL for spark 3
spark-sql --packages
org.apache.hudi:hudi-spark3-bundle_2.12:0.10.0,org.apache.spark:spark-avro_2.12:3.1.2
\
--conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' \
--conf
'spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension'
-# spark-sql for spark 2 with scala 2.11
+# Spark SQL for spark 2 with scala 2.11
spark-sql --packages
org.apache.hudi:hudi-spark-bundle_2.11:0.10.0,org.apache.spark:spark-avro_2.11:2.4.4
\
--conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' \
--conf
'spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension'
-# spark-sql for spark 2 with scala 2.12
+# Spark SQL for spark 2 with scala 2.12
spark-sql \
--packages
org.apache.hudi:hudi-spark-bundle_2.12:0.10.0,org.apache.spark:spark-avro_2.12:2.4.4
\
--conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' \
@@ -276,7 +276,7 @@ You don't need to specify schema and any properties except
the partitioned colum
**CTAS**
-Hudi supports CTAS (Create Table As Select) on spark sql. <br/>
+Hudi supports CTAS (Create Table As Select) on Spark SQL. <br/>
Note: For better performance to load data to hudi table, CTAS uses the **bulk
insert** as the write operation.
Example CTAS command to create a non-partitioned COW table without
preCombineField.
@@ -599,7 +599,7 @@ denoted by the timestamp. Look for changes in
`_hoodie_commit_time`, `rider`, `d
</TabItem>
<TabItem value="sparksql">
-Spark sql supports two kinds of DML to update hudi table: Merge-Into and
Update.
+Spark SQL supports two kinds of DML to update hudi table: Merge-Into and
Update.
### Update
**Syntax**
