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Posted to commits@spark.apache.org by gu...@apache.org on 2020/08/22 01:10:34 UTC

[spark] branch branch-3.0 updated: [MINOR][DOCS] backport PR#29443 to fix typo in doc, log messages and comments

This is an automated email from the ASF dual-hosted git repository.

gurwls223 pushed a commit to branch branch-3.0
in repository https://gitbox.apache.org/repos/asf/spark.git


The following commit(s) were added to refs/heads/branch-3.0 by this push:
     new 9ccc790  [MINOR][DOCS] backport PR#29443 to fix typo in doc,log messages and comments
9ccc790 is described below

commit 9ccc79036f0c562b4b3d0e38c8fdfbb70f6e3319
Author: Brandon Jiang <br...@users.noreply.github.com>
AuthorDate: Sat Aug 22 10:08:39 2020 +0900

    [MINOR][DOCS] backport PR#29443 to fix typo in doc,log messages and comments
    
    ### What changes were proposed in this pull request?
    backport PR #29443 to fix typo for docs, log messages and comments
    
    ### Why are the changes needed?
    typo fix to increase readability
    
    ### Does this PR introduce _any_ user-facing change?
    No
    
    ### How was this patch tested?
    manual test has been performed to test the updated
    
    Closes #29512 from brandonJY/branch-3.0.
    
    Authored-by: Brandon Jiang <br...@users.noreply.github.com>
    Signed-off-by: HyukjinKwon <gu...@apache.org>
---
 .../src/main/java/org/apache/spark/network/util/TransportConf.java      | 2 +-
 core/src/main/java/org/apache/spark/api/plugin/DriverPlugin.java        | 2 +-
 .../scala/org/apache/spark/resource/ResourceDiscoveryScriptPlugin.scala | 2 +-
 docs/job-scheduling.md                                                  | 2 +-
 docs/sql-ref-syntax-qry-select-groupby.md                               | 2 +-
 docs/sql-ref-syntax-qry-select-hints.md                                 | 2 +-
 docs/sql-ref.md                                                         | 2 +-
 launcher/src/main/java/org/apache/spark/launcher/LauncherServer.java    | 2 +-
 .../main/java/org/apache/spark/sql/connector/catalog/TableCatalog.java  | 2 +-
 .../main/scala/org/apache/spark/sql/catalyst/QueryPlanningTracker.scala | 2 +-
 .../spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala    | 2 +-
 11 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/common/network-common/src/main/java/org/apache/spark/network/util/TransportConf.java b/common/network-common/src/main/java/org/apache/spark/network/util/TransportConf.java
index 6c37f9a..646e427 100644
--- a/common/network-common/src/main/java/org/apache/spark/network/util/TransportConf.java
+++ b/common/network-common/src/main/java/org/apache/spark/network/util/TransportConf.java
@@ -290,7 +290,7 @@ public class TransportConf {
   }
 
   /**
-  * If enabled then off-heap byte buffers will be prefered for the shared ByteBuf allocators.
+  * If enabled then off-heap byte buffers will be preferred for the shared ByteBuf allocators.
   */
   public boolean preferDirectBufsForSharedByteBufAllocators() {
     return conf.getBoolean("spark.network.io.preferDirectBufs", true);
diff --git a/core/src/main/java/org/apache/spark/api/plugin/DriverPlugin.java b/core/src/main/java/org/apache/spark/api/plugin/DriverPlugin.java
index 0c0d0df..1d676ff 100644
--- a/core/src/main/java/org/apache/spark/api/plugin/DriverPlugin.java
+++ b/core/src/main/java/org/apache/spark/api/plugin/DriverPlugin.java
@@ -41,7 +41,7 @@ public interface DriverPlugin {
    * initialization.
    * <p>
    * It's recommended that plugins be careful about what operations are performed in this call,
-   * preferrably performing expensive operations in a separate thread, or postponing them until
+   * preferably performing expensive operations in a separate thread, or postponing them until
    * the application has fully started.
    *
    * @param sc The SparkContext loading the plugin.
diff --git a/core/src/main/scala/org/apache/spark/resource/ResourceDiscoveryScriptPlugin.scala b/core/src/main/scala/org/apache/spark/resource/ResourceDiscoveryScriptPlugin.scala
index 11a9bb8..d861e91 100644
--- a/core/src/main/scala/org/apache/spark/resource/ResourceDiscoveryScriptPlugin.scala
+++ b/core/src/main/scala/org/apache/spark/resource/ResourceDiscoveryScriptPlugin.scala
@@ -29,7 +29,7 @@ import org.apache.spark.util.Utils.executeAndGetOutput
 /**
  * The default plugin that is loaded into a Spark application to control how custom
  * resources are discovered. This executes the discovery script specified by the user
- * and gets the json output back and contructs ResourceInformation objects from that.
+ * and gets the json output back and constructs ResourceInformation objects from that.
  * If the user specifies custom plugins, this is the last one to be executed and
  * throws if the resource isn't discovered.
  *
diff --git a/docs/job-scheduling.md b/docs/job-scheduling.md
index eaacfa4..5c19c77 100644
--- a/docs/job-scheduling.md
+++ b/docs/job-scheduling.md
@@ -95,7 +95,7 @@ varies across cluster managers:
 In standalone mode, simply start your workers with `spark.shuffle.service.enabled` set to `true`.
 
 In Mesos coarse-grained mode, run `$SPARK_HOME/sbin/start-mesos-shuffle-service.sh` on all
-slave nodes with `spark.shuffle.service.enabled` set to `true`. For instance, you may do so
+worker nodes with `spark.shuffle.service.enabled` set to `true`. For instance, you may do so
 through Marathon.
 
 In YARN mode, follow the instructions [here](running-on-yarn.html#configuring-the-external-shuffle-service).
diff --git a/docs/sql-ref-syntax-qry-select-groupby.md b/docs/sql-ref-syntax-qry-select-groupby.md
index 6137c0d..934e5f7 100644
--- a/docs/sql-ref-syntax-qry-select-groupby.md
+++ b/docs/sql-ref-syntax-qry-select-groupby.md
@@ -58,7 +58,7 @@ aggregate_name ( [ DISTINCT ] expression [ , ... ] ) [ FILTER ( WHERE boolean_ex
 
 * **grouping_expression**
 
-    Specifies the critieria based on which the rows are grouped together. The grouping of rows is performed based on
+    Specifies the criteria based on which the rows are grouped together. The grouping of rows is performed based on
     result values of the grouping expressions. A grouping expression may be a column alias, a column position
     or an expression.
 
diff --git a/docs/sql-ref-syntax-qry-select-hints.md b/docs/sql-ref-syntax-qry-select-hints.md
index 247ce48..5f1cb4c 100644
--- a/docs/sql-ref-syntax-qry-select-hints.md
+++ b/docs/sql-ref-syntax-qry-select-hints.md
@@ -31,7 +31,7 @@ Hints give users a way to suggest how Spark SQL to use specific approaches to ge
 
 ### Partitioning Hints
 
-Partitioning hints allow users to suggest a partitioning stragety that Spark should follow. `COALESCE`, `REPARTITION`,
+Partitioning hints allow users to suggest a partitioning strategy that Spark should follow. `COALESCE`, `REPARTITION`,
 and `REPARTITION_BY_RANGE` hints are supported and are equivalent to `coalesce`, `repartition`, and
 `repartitionByRange` [Dataset APIs](api/scala/org/apache/spark/sql/Dataset.html), respectively. These hints give users
 a way to tune performance and control the number of output files in Spark SQL. When multiple partitioning hints are
diff --git a/docs/sql-ref.md b/docs/sql-ref.md
index 8d0c673..6a87166 100644
--- a/docs/sql-ref.md
+++ b/docs/sql-ref.md
@@ -32,7 +32,7 @@ Spark SQL is Apache Spark's module for working with structured data. This guide
    * [Integration with Hive UDFs/UDAFs/UDTFs](sql-ref-functions-udf-hive.html)
  * [Identifiers](sql-ref-identifier.html)
  * [Literals](sql-ref-literals.html)
- * [Null Semanitics](sql-ref-null-semantics.html)
+ * [Null Semantics](sql-ref-null-semantics.html)
  * [SQL Syntax](sql-ref-syntax.html)
    * [DDL Statements](sql-ref-syntax-ddl.html)
    * [DML Statements](sql-ref-syntax-dml.html)
diff --git a/launcher/src/main/java/org/apache/spark/launcher/LauncherServer.java b/launcher/src/main/java/org/apache/spark/launcher/LauncherServer.java
index 3ff7787..d5a277b 100644
--- a/launcher/src/main/java/org/apache/spark/launcher/LauncherServer.java
+++ b/launcher/src/main/java/org/apache/spark/launcher/LauncherServer.java
@@ -364,7 +364,7 @@ class LauncherServer implements Closeable {
      *
      * This method allows a short period for the above to happen (same amount of time as the
      * connection timeout, which is configurable). This should be fine for well-behaved
-     * applications, where they close the connection arond the same time the app handle detects the
+     * applications, where they close the connection around the same time the app handle detects the
      * app has finished.
      *
      * In case the connection is not closed within the grace period, this method forcefully closes
diff --git a/sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/TableCatalog.java b/sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/TableCatalog.java
index 1809b9c..b818515 100644
--- a/sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/TableCatalog.java
+++ b/sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/TableCatalog.java
@@ -176,7 +176,7 @@ public interface TableCatalog extends CatalogPlugin {
    * @param newIdent the new table identifier of the table
    * @throws NoSuchTableException If the table to rename doesn't exist or is a view
    * @throws TableAlreadyExistsException If the new table name already exists or is a view
-   * @throws UnsupportedOperationException If the namespaces of old and new identiers do not
+   * @throws UnsupportedOperationException If the namespaces of old and new identifiers do not
    *                                       match (optional)
    */
   void renameTable(Identifier oldIdent, Identifier newIdent)
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/QueryPlanningTracker.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/QueryPlanningTracker.scala
index cd75407c..35551d8 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/QueryPlanningTracker.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/QueryPlanningTracker.scala
@@ -28,7 +28,7 @@ import org.apache.spark.util.BoundedPriorityQueue
  * There are two separate concepts we track:
  *
  * 1. Phases: These are broad scope phases in query planning, as listed below, i.e. analysis,
- * optimizationm and physical planning (just planning).
+ * optimization and physical planning (just planning).
  *
  * 2. Rules: These are the individual Catalyst rules that we track. In addition to time, we also
  * track the number of invocations and effective invocations.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
index fef63cb..95715fd 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
@@ -36,7 +36,7 @@ case class ShowTablePropertiesExec(
     import scala.collection.JavaConverters._
     val toRow = RowEncoder(schema).resolveAndBind().createSerializer()
 
-    // The reservered properties are accessible through DESCRIBE
+    // The reserved properties are accessible through DESCRIBE
     val properties = catalogTable.properties.asScala
       .filter { case (k, v) => !CatalogV2Util.TABLE_RESERVED_PROPERTIES.contains(k) }
     propertyKey match {


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