From dc1ba9e9fc169962a9282ea6644dce09281ff598 Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Thu, 4 Sep 2014 15:06:08 -0700 Subject: [PATCH] [SPARK-3378] [DOCS] Replace the word "SparkSQL" with right word "Spark SQL" Author: Kousuke Saruta Closes #2251 from sarutak/SPARK-3378 and squashes the following commits: 0bfe234 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3378 bb5938f [Kousuke Saruta] Replaced rest of "SparkSQL" with "Spark SQL" 6df66de [Kousuke Saruta] Replaced "SparkSQL" with "Spark SQL" --- dev/run-tests | 2 +- docs/programming-guide.md | 2 +- python/pyspark/sql.py | 6 +++--- python/run-tests | 2 +- .../src/main/scala/org/apache/spark/sql/api/java/Row.scala | 2 +- .../apache/spark/sql/hive/parquet/FakeParquetSerDe.scala | 2 +- 6 files changed, 8 insertions(+), 8 deletions(-) diff --git a/dev/run-tests b/dev/run-tests index d751961605dfd..90a8ce16f0f06 100755 --- a/dev/run-tests +++ b/dev/run-tests @@ -89,7 +89,7 @@ echo "=========================================================================" echo "Running Spark unit tests" echo "=========================================================================" -# Build Spark; we always build with Hive because the PySpark SparkSQL tests need it. +# Build Spark; we always build with Hive because the PySpark Spark SQL tests need it. # echo "q" is needed because sbt on encountering a build file with failure # (either resolution or compilation) prompts the user for input either q, r, # etc to quit or retry. This echo is there to make it not block. diff --git a/docs/programming-guide.md b/docs/programming-guide.md index 6ae780d94046a..624cc744dfd51 100644 --- a/docs/programming-guide.md +++ b/docs/programming-guide.md @@ -385,7 +385,7 @@ Apart from text files, Spark's Python API also supports several other data forma * SequenceFile and Hadoop Input/Output Formats -**Note** this feature is currently marked ```Experimental``` and is intended for advanced users. It may be replaced in future with read/write support based on SparkSQL, in which case SparkSQL is the preferred approach. +**Note** this feature is currently marked ```Experimental``` and is intended for advanced users. It may be replaced in future with read/write support based on Spark SQL, in which case Spark SQL is the preferred approach. **Writable Support** diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index aaa35dadc203e..e7f573cf6da44 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -900,7 +900,7 @@ def __reduce__(self): class SQLContext: - """Main entry point for SparkSQL functionality. + """Main entry point for Spark SQL functionality. A SQLContext can be used create L{SchemaRDD}s, register L{SchemaRDD}s as tables, execute SQL over tables, cache tables, and read parquet files. @@ -946,7 +946,7 @@ def __init__(self, sparkContext, sqlContext=None): @property def _ssql_ctx(self): - """Accessor for the JVM SparkSQL context. + """Accessor for the JVM Spark SQL context. Subclasses can override this property to provide their own JVM Contexts. @@ -1507,7 +1507,7 @@ class SchemaRDD(RDD): """An RDD of L{Row} objects that has an associated schema. The underlying JVM object is a SchemaRDD, not a PythonRDD, so we can - utilize the relational query api exposed by SparkSQL. + utilize the relational query api exposed by Spark SQL. For normal L{pyspark.rdd.RDD} operations (map, count, etc.) the L{SchemaRDD} is not operated on directly, as it's underlying diff --git a/python/run-tests b/python/run-tests index d671da40031c8..f2a80b4f1838b 100755 --- a/python/run-tests +++ b/python/run-tests @@ -28,7 +28,7 @@ FAILED=0 rm -f unit-tests.log -# Remove the metastore and warehouse directory created by the HiveContext tests in SparkSQL +# Remove the metastore and warehouse directory created by the HiveContext tests in Spark SQL rm -rf metastore warehouse function run_test() { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala index 6c67934bda5b8..e9d04ce7aae4c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala @@ -25,7 +25,7 @@ import scala.math.BigDecimal import org.apache.spark.sql.catalyst.expressions.{Row => ScalaRow} /** - * A result row from a SparkSQL query. + * A result row from a Spark SQL query. */ class Row(private[spark] val row: ScalaRow) extends Serializable { diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala index 544abfc32423c..abed299cd957f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala @@ -26,7 +26,7 @@ import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector import org.apache.hadoop.io.Writable /** - * A placeholder that allows SparkSQL users to create metastore tables that are stored as + * A placeholder that allows Spark SQL users to create metastore tables that are stored as * parquet files. It is only intended to pass the checks that the serde is valid and exists * when a CREATE TABLE is run. The actual work of decoding will be done by ParquetTableScan * when "spark.sql.hive.convertMetastoreParquet" is set to true.