Override QueryExecution with special debug workflow.
Caches the specified table in-memory.
Caches the specified table in-memory.
Sets up the system initially or after a RESET command
Sets up the system initially or after a RESET command
:: Experimental ::
Creates an empty parquet file with the schema of class A
, which can be registered as a table.
:: Experimental ::
Creates an empty parquet file with the schema of class A
, which can be registered as a table.
This registered table can be used as the target of future insertInto
operations.
val sqlContext = new SQLContext(...) import sqlContext._ case class Person(name: String, age: Int) createParquetFile[Person]("path/to/file.parquet").registerAsTable("people") sql("INSERT INTO people SELECT 'michael', 29")
A case class type that describes the desired schema of the parquet file to be created.
The path where the directory containing parquet metadata should be created. Data inserted into this table will also be stored at this location.
When false, an exception will be thrown if this directory already exists.
A Hadoop configuration object that can be used to specify options to the parquet output format.
Creates a SchemaRDD from an RDD of case classes.
Creates a SchemaRDD from an RDD of case classes.
Creates a table using the schema of the given class.
Creates a table using the schema of the given class.
A case class that is used to describe the schema of the table to be created.
The name of the table to create.
When false, an exception will be thrown if the table already exists.
The location of the hive source code.
The location of the compiled hive distribution
Executes a query expressed in HiveQL using Spark, returning the result as a SchemaRDD.
Executes a query expressed in HiveQL using Spark, returning the result as a SchemaRDD.
An alias for hiveql
.
An alias for hiveql
.
:: DeveloperApi :: Allows catalyst LogicalPlans to be executed as a SchemaRDD.
:: DeveloperApi :: Allows catalyst LogicalPlans to be executed as a SchemaRDD. Note that the LogicalPlan interface is considered internal, and thus not guaranteed to be stable. As a result, using them directly is not recommended.
Records the UDFs present when the server starts, so we can delete ones that are created by tests.
Records the UDFs present when the server starts, so we can delete ones that are created by tests.
Loads a Parquet file, returning the result as a SchemaRDD.
Loads a Parquet file, returning the result as a SchemaRDD.
Prepares a planned SparkPlan for execution by binding references to specific ordinals, and inserting shuffle operations as needed.
Prepares a planned SparkPlan for execution by binding references to specific ordinals, and inserting shuffle operations as needed.
Registers the given RDD as a temporary table in the catalog.
Registers the given RDD as a temporary table in the catalog. Temporary tables exist only during the lifetime of this instance of SQLContext.
Resets the test instance by deleting any tables that have been created.
Resets the test instance by deleting any tables that have been created. TODO: also clear out UDFs, views, etc.
Execute the command using Hive and return the results as a sequence.
Execute the command using Hive and return the results as a sequence. Each element in the sequence is one row.
Runs the specified SQL query using Hive.
Runs the specified SQL query using Hive.
Executes a SQL query using Spark, returning the result as a SchemaRDD.
Executes a SQL query using Spark, returning the result as a SchemaRDD.
Returns the specified table as a SchemaRDD
Returns the specified table as a SchemaRDD
A list of test tables and the DDL required to initialize them.
A list of test tables and the DDL required to initialize them. A test table is loaded on demand when a query are run against it.
Removes the specified table from the in-memory cache.
Removes the specified table from the in-memory cache.
A locally running test instance of Spark's Hive execution engine.
Data from testTables will be automatically loaded whenever a query is run over those tables. Calling reset will delete all tables and other state in the database, leaving the database in a "clean" state.
TestHive is singleton object version of this class because instantiating multiple copies of the hive metastore seems to lead to weird non-deterministic failures. Therefore, the execution of test cases that rely on TestHive must be serialized.