Replaced rest of "SparkSQL" with "Spark SQL"

Author: sarutak

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.

python/pyspark/sql.py

@@ -901,7 +901,7 @@ 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.
@@ -949,7 +949,7 @@ 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.
@@ -1492,7 +1492,7 @@ 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

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() {

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 {
 

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.