Revert "[SPARK-2410][SQL] Merging Hive Thrift/JDBC server"

This reverts commit f6ff2a61d00d12481bfb211ae13d6992daacdcc2.

1 files changed, 3 insertions, 198 deletions

diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index 156e0aebde..38728534a4 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -136,7 +136,7 @@ val sqlContext = new org.apache.spark.sql.SQLContext(sc)
 import sqlContext.createSchemaRDD
 
 // Define the schema using a case class.
-// Note: Case classes in Scala 2.10 can support only up to 22 fields. To work around this limit,
+// Note: Case classes in Scala 2.10 can support only up to 22 fields. To work around this limit, 
 // you can use custom classes that implement the Product interface.
 case class Person(name: String, age: Int)
 
@@ -548,6 +548,7 @@ results = hiveContext.hql("FROM src SELECT key, value").collect()
 </div>
 </div>
 
+
 # Writing Language-Integrated Relational Queries
 
 **Language-Integrated queries are currently only supported in Scala.**
@@ -572,200 +573,4 @@ prefixed with a tick (`'`).  Implicit conversions turn these symbols into expres
 evaluated by the SQL execution engine.  A full list of the functions supported can be found in the
 [ScalaDoc](api/scala/index.html#org.apache.spark.sql.SchemaRDD).
 
-<!-- TODO: Include the table of operations here. -->
-
-## Running the Thrift JDBC server
-
-The Thrift JDBC server implemented here corresponds to the [`HiveServer2`]
-(https://cwiki.apache.org/confluence/display/Hive/Setting+Up+HiveServer2) in Hive 0.12. You can test
-the JDBC server with the beeline script comes with either Spark or Hive 0.12.  In order to use Hive
-you must first run '`sbt/sbt -Phive-thriftserver assembly/assembly`' (or use `-Phive-thriftserver`
-for maven).
-
-To start the JDBC server, run the following in the Spark directory:
-
-    ./sbin/start-thriftserver.sh
-
-The default port the server listens on is 10000.  To listen on customized host and port, please set
-the `HIVE_SERVER2_THRIFT_PORT` and `HIVE_SERVER2_THRIFT_BIND_HOST` environment variables. You may
-run `./sbin/start-thriftserver.sh --help` for a complete list of all available options.  Now you can
-use beeline to test the Thrift JDBC server:
-
-    ./bin/beeline
-
-Connect to the JDBC server in beeline with:
-
-    beeline> !connect jdbc:hive2://localhost:10000
-
-Beeline will ask you for a username and password. In non-secure mode, simply enter the username on
-your machine and a blank password. For secure mode, please follow the instructions given in the
-[beeline documentation](https://cwiki.apache.org/confluence/display/Hive/HiveServer2+Clients)
-
-Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`.
-
-You may also use the beeline script comes with Hive.
-
-### Migration Guide for Shark Users
-
-#### Reducer number
-
-In Shark, default reducer number is 1 and is controlled by the property `mapred.reduce.tasks`. Spark
-SQL deprecates this property by a new property `spark.sql.shuffle.partitions`, whose default value
-is 200. Users may customize this property via `SET`:
-
-```
-SET spark.sql.shuffle.partitions=10;
-SELECT page, count(*) c FROM logs_last_month_cached
-GROUP BY page ORDER BY c DESC LIMIT 10;
-```
-
-You may also put this property in `hive-site.xml` to override the default value.
-
-For now, the `mapred.reduce.tasks` property is still recognized, and is converted to
-`spark.sql.shuffle.partitions` automatically.
-
-#### Caching
-
-The `shark.cache` table property no longer exists, and tables whose name end with `_cached` are no
-longer automcatically cached. Instead, we provide `CACHE TABLE` and `UNCACHE TABLE` statements to
-let user control table caching explicitly:
-
-```
-CACHE TABLE logs_last_month;
-UNCACHE TABLE logs_last_month;
-```
-
-**NOTE** `CACHE TABLE tbl` is lazy, it only marks table `tbl` as "need to by cached if necessary",
-but doesn't actually cache it until a query that touches `tbl` is executed. To force the table to be
-cached, you may simply count the table immediately after executing `CACHE TABLE`:
-
-```
-CACHE TABLE logs_last_month;
-SELECT COUNT(1) FROM logs_last_month;
-```
-
-Several caching related features are not supported yet:
-
-* User defined partition level cache eviction policy
-* RDD reloading
-* In-memory cache write through policy
-
-### Compatibility with Apache Hive
-
-#### Deploying in Exising Hive Warehouses
-
-Spark SQL Thrift JDBC server is designed to be "out of the box" compatible with existing Hive
-installations. You do not need to modify your existing Hive Metastore or change the data placement
-or partitioning of your tables.
-
-#### Supported Hive Features
-
-Spark SQL supports the vast majority of Hive features, such as:
-
-* Hive query statements, including:
- * `SELECT`
- * `GROUP BY
- * `ORDER BY`
- * `CLUSTER BY`
- * `SORT BY`
-* All Hive operators, including:
- * Relational operators (`=`, `⇔`, `==`, `<>`, `<`, `>`, `>=`, `<=`, etc)
- * Arthimatic operators (`+`, `-`, `*`, `/`, `%`, etc)
- * Logical operators (`AND`, `&&`, `OR`, `||`, etc)
- * Complex type constructors
- * Mathemtatical functions (`sign`, `ln`, `cos`, etc)
- * String functions (`instr`, `length`, `printf`, etc)
-* User defined functions (UDF)
-* User defined aggregation functions (UDAF)
-* User defined serialization formats (SerDe's)
-* Joins
- * `JOIN`
- * `{LEFT|RIGHT|FULL} OUTER JOIN`
- * `LEFT SEMI JOIN`
- * `CROSS JOIN`
-* Unions
-* Sub queries
- * `SELECT col FROM ( SELECT a + b AS col from t1) t2`
-* Sampling
-* Explain
-* Partitioned tables
-* All Hive DDL Functions, including:
- * `CREATE TABLE`
- * `CREATE TABLE AS SELECT`
- * `ALTER TABLE`
-* Most Hive Data types, including:
- * `TINYINT`
- * `SMALLINT`
- * `INT`
- * `BIGINT`
- * `BOOLEAN`
- * `FLOAT`
- * `DOUBLE`
- * `STRING`
- * `BINARY`
- * `TIMESTAMP`
- * `ARRAY<>`
- * `MAP<>`
- * `STRUCT<>`
-
-#### Unsupported Hive Functionality
-
-Below is a list of Hive features that we don't support yet. Most of these features are rarely used
-in Hive deployments.
-
-**Major Hive Features**
-
-* Tables with buckets: bucket is the hash partitioning within a Hive table partition. Spark SQL
-  doesn't support buckets yet.
-
-**Esoteric Hive Features**
-
-* Tables with partitions using different input formats: In Spark SQL, all table partitions need to
-  have the same input format.
-* Non-equi outer join: For the uncommon use case of using outer joins with non-equi join conditions
-  (e.g. condition "`key < 10`"), Spark SQL will output wrong result for the `NULL` tuple.
-* `UNIONTYPE`
-* Unique join
-* Single query multi insert
-* Column statistics collecting: Spark SQL does not piggyback scans to collect column statistics at
-  the moment.
-
-**Hive Input/Output Formats**
-
-* File format for CLI: For results showing back to the CLI, Spark SQL only supports TextOutputFormat.
-* Hadoop archive
-
-**Hive Optimizations**
-
-A handful of Hive optimizations are not yet included in Spark. Some of these (such as indexes) are
-not necessary due to Spark SQL's in-memory computational model. Others are slotted for future
-releases of Spark SQL.
-
-* Block level bitmap indexes and virtual columns (used to build indexes)
-* Automatically convert a join to map join: For joining a large table with multiple small tables,
-  Hive automatically converts the join into a map join. We are adding this auto conversion in the
-  next release.
-* Automatically determine the number of reducers for joins and groupbys: Currently in Spark SQL, you
-  need to control the degree of parallelism post-shuffle using "SET
-  spark.sql.shuffle.partitions=[num_tasks];". We are going to add auto-setting of parallelism in the
-  next release.
-* Meta-data only query: For queries that can be answered by using only meta data, Spark SQL still
-  launches tasks to compute the result.
-* Skew data flag: Spark SQL does not follow the skew data flags in Hive.
-* `STREAMTABLE` hint in join: Spark SQL does not follow the `STREAMTABLE` hint.
-* Merge multiple small files for query results: if the result output contains multiple small files,
-  Hive can optionally merge the small files into fewer large files to avoid overflowing the HDFS
-  metadata. Spark SQL does not support that.
-
-## Running the Spark SQL CLI
-
-The Spark SQL CLI is a convenient tool to run the Hive metastore service in local mode and execute
-queries input from command line. Note: the Spark SQL CLI cannot talk to the Thrift JDBC server.
-
-To start the Spark SQL CLI, run the following in the Spark directory:
-
-    ./bin/spark-sql
-
-Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`.
-You may run `./bin/spark-sql --help` for a complete list of all available
-options.
+<!-- TODO: Include the table of operations here. -->
\ No newline at end of file