Resolve conflict.

core/src/main/scala/org/apache/spark/internal/Logging.scala

@@ -117,7 +117,7 @@ trait Logging {
   }
 
   // For testing
-  def initializeForcefully(isInterpreter: Boolean, silent: Boolean): Unit = {
+  private[spark] def initializeForcefully(isInterpreter: Boolean, silent: Boolean): Unit = {
     initializeLogging(isInterpreter, silent)
   }
 

core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala

@@ -502,7 +502,6 @@ private[serializer] object KryoSerializer {
       "org.apache.spark.ml.attribute.NumericAttribute",
 
       "org.apache.spark.ml.feature.Instance",
-      "org.apache.spark.ml.feature.InstanceBlock",
       "org.apache.spark.ml.feature.LabeledPoint",
       "org.apache.spark.ml.feature.OffsetInstance",
       "org.apache.spark.ml.linalg.DenseMatrix",

dev/deps/spark-deps-hadoop-2.7-hive-2.3

@@ -87,7 +87,6 @@ hive-jdbc/2.3.6//hive-jdbc-2.3.6.jar
 hive-llap-common/2.3.6//hive-llap-common-2.3.6.jar
 hive-metastore/2.3.6//hive-metastore-2.3.6.jar
 hive-serde/2.3.6//hive-serde-2.3.6.jar
-hive-service-rpc/2.3.6//hive-service-rpc-2.3.6.jar
 hive-shims-0.23/2.3.6//hive-shims-0.23-2.3.6.jar
 hive-shims-common/2.3.6//hive-shims-common-2.3.6.jar
 hive-shims-scheduler/2.3.6//hive-shims-scheduler-2.3.6.jar

dev/deps/spark-deps-hadoop-3.2-hive-2.3

@@ -86,7 +86,6 @@ hive-jdbc/2.3.6//hive-jdbc-2.3.6.jar
 hive-llap-common/2.3.6//hive-llap-common-2.3.6.jar
 hive-metastore/2.3.6//hive-metastore-2.3.6.jar
 hive-serde/2.3.6//hive-serde-2.3.6.jar
-hive-service-rpc/2.3.6//hive-service-rpc-2.3.6.jar
 hive-shims-0.23/2.3.6//hive-shims-0.23-2.3.6.jar
 hive-shims-common/2.3.6//hive-shims-common-2.3.6.jar
 hive-shims-scheduler/2.3.6//hive-shims-scheduler-2.3.6.jar

dev/sparktestsupport/modules.py

@@ -364,7 +364,6 @@ def __hash__(self):
         "pyspark.sql.avro.functions",
         "pyspark.sql.pandas.conversion",
         "pyspark.sql.pandas.map_ops",
-        "pyspark.sql.pandas.functions",
         "pyspark.sql.pandas.group_ops",
         "pyspark.sql.pandas.types",
         "pyspark.sql.pandas.serializers",

docs/.gitignore

@@ -0,0 +1 @@
+sql-configs.html

docs/configuration.md

@@ -2399,47 +2399,15 @@ the driver or executor, or, in the absence of that value, the number of cores av
 Please refer to the [Security](security.html) page for available options on how to secure different
 Spark subsystems.
 
-### Spark SQL
-
-Running the <code>SET -v</code> command will show the entire list of the SQL configuration.
-
-<div class="codetabs">
-<div data-lang="scala"  markdown="1">
 
-{% highlight scala %}
-// spark is an existing SparkSession
-spark.sql("SET -v").show(numRows = 200, truncate = false)
-{% endhighlight %}
-
-</div>
-
-<div data-lang="java"  markdown="1">
-
-{% highlight java %}
-// spark is an existing SparkSession
-spark.sql("SET -v").show(200, false);
-{% endhighlight %}
-</div>
-
-<div data-lang="python"  markdown="1">
-
-{% highlight python %}
-# spark is an existing SparkSession
-spark.sql("SET -v").show(n=200, truncate=False)
-{% endhighlight %}
-
-</div>
-
-<div data-lang="r"  markdown="1">
-
-{% highlight r %}
-sparkR.session()
-properties <- sql("SET -v")
-showDF(properties, numRows = 200, truncate = FALSE)
-{% endhighlight %}
+{% for static_file in site.static_files %}
+    {% if static_file.name == 'sql-configs.html' %}
+### Spark SQL
 
-</div>
-</div>
+        {% include_relative sql-configs.html %}
+        {% break %}
+    {% endif %}
+{% endfor %}
 
 
 ### Spark Streaming

docs/sql-migration-guide.md

@@ -101,7 +101,7 @@ license: |
 
   - Since Spark 3.0, if files or subdirectories disappear during recursive directory listing (i.e. they appear in an intermediate listing but then cannot be read or listed during later phases of the recursive directory listing, due to either concurrent file deletions or object store consistency issues) then the listing will fail with an exception unless `spark.sql.files.ignoreMissingFiles` is `true` (default `false`). In previous versions, these missing files or subdirectories would be ignored. Note that this change of behavior only applies during initial table file listing (or during `REFRESH TABLE`), not during query execution: the net change is that `spark.sql.files.ignoreMissingFiles` is now obeyed during table file listing / query planning, not only at query execution time.
 
-  - Since Spark 3.0, substitution order of nested WITH clauses is changed and an inner CTE definition takes precedence over an outer. In version 2.4 and earlier, `WITH t AS (SELECT 1), t2 AS (WITH t AS (SELECT 2) SELECT * FROM t) SELECT * FROM t2` returns `1` while in version 3.0 it returns `2`. The previous behaviour can be restored by setting `spark.sql.legacy.ctePrecedence.enabled` to `true`.
+  - Since Spark 3.0, Spark throws an AnalysisException if name conflict is detected in the nested WITH clause by default. It forces the users to choose the specific substitution order they wanted, which is controlled by `spark.sql.legacy.ctePrecedence.enabled`. If set to false (which is recommended), inner CTE definitions take precedence over outer definitions. For example, set the config to `false`, `WITH t AS (SELECT 1), t2 AS (WITH t AS (SELECT 2) SELECT * FROM t) SELECT * FROM t2` returns `2`, while setting it to `true`, the result is `1` which is the behavior in version 2.4 and earlier.
 
   - Since Spark 3.0, the `add_months` function does not adjust the resulting date to a last day of month if the original date is a last day of months. For example, `select add_months(DATE'2019-02-28', 1)` results `2019-03-28`. In Spark version 2.4 and earlier, the resulting date is adjusted when the original date is a last day of months. For example, adding a month to `2019-02-28` results in `2019-03-31`.
 
@@ -215,6 +215,8 @@ license: |
   For example `SELECT timestamp 'tomorrow';`.
 
   - Since Spark 3.0, the `size` function returns `NULL` for the `NULL` input. In Spark version 2.4 and earlier, this function gives `-1` for the same input. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.sizeOfNull` to `true`.
+
+  - Since Spark 3.0, when the `array` function is called without any parameters, it returns an empty array of `NullType`. In Spark version 2.4 and earlier, it returns an empty array of string type. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.arrayDefaultToStringType.enabled` to `true`.
 
   - Since Spark 3.0, the interval literal syntax does not allow multiple from-to units anymore. For example, `SELECT INTERVAL '1-1' YEAR TO MONTH '2-2' YEAR TO MONTH'` throws parser exception.
 
@@ -326,7 +328,7 @@ license: |
 
   - Since Spark 3.0, `SHOW TBLPROPERTIES` will cause `AnalysisException` if the table does not exist. In Spark version 2.4 and earlier, this scenario caused `NoSuchTableException`. Also, `SHOW TBLPROPERTIES` on a temporary view will cause `AnalysisException`. In Spark version 2.4 and earlier, it returned an empty result.
 
-  - Since Spark 3.0, `SHOW CREATE TABLE` will always return Spark DDL, even when the given table is a Hive serde table. For Hive DDL, please use `SHOW CREATE TABLE AS SERDE` command instead.
+  - Since Spark 3.0, `SHOW CREATE TABLE` will always return Spark DDL, even when the given table is a Hive serde table. For generating Hive DDL, please use `SHOW CREATE TABLE AS SERDE` command instead.
 
   - Since Spark 3.0, we upgraded the built-in Hive from 1.2 to 2.3. This may need to set `spark.sql.hive.metastore.version` and `spark.sql.hive.metastore.jars` according to the version of the Hive metastore.
   For example: set `spark.sql.hive.metastore.version` to `1.2.1` and `spark.sql.hive.metastore.jars` to `maven` if your Hive metastore version is 1.2.1.