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## What changes were proposed in this pull request? This PR fixes all the instances which was fixed in the previous PR. To make sure, I manually debugged and also checked the Scala source. `length` in [LinearSeqOptimized.scala#L49-L57](https://github.com/scala/scala/blob/2.11.x/src/library/scala/collection/LinearSeqOptimized.scala#L49-L57) is O(n). Also, `size` calls `length` via [SeqLike.scala#L106](https://github.com/scala/scala/blob/2.11.x/src/library/scala/collection/SeqLike.scala#L106). For debugging, I have created these as below: ```scala ArrayBuffer(1, 2, 3) Array(1, 2, 3) List(1, 2, 3) Seq(1, 2, 3) ``` and then called `size` and `length` for each to debug. ## How was this patch tested? I ran the bash as below on Mac ```bash find . -name *.scala -type f -exec grep -il "while (.*\\.length)" {} \; | grep "src/main" find . -name *.scala -type f -exec grep -il "while (.*\\.size)" {} \; | grep "src/main" ``` and then checked each. Author: hyukjinkwon <gurwls223@gmail.com> Closes #15093 from HyukjinKwon/SPARK-17480-followup. |
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catalyst | ||
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hive | ||
hive-thriftserver | ||
README.md |
Spark SQL
This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.
Spark SQL is broken up into four subprojects:
- Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
- Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
- Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
- HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.