d1f6c64c4b
## What changes were proposed in this pull request?
Since we could not directly define the array type in R, this PR proposes to support array types in R as string types that are used in `structField` as below:
```R
jsonArr <- "[{\"name\":\"Bob\"}, {\"name\":\"Alice\"}]"
df <- as.DataFrame(list(list("people" = jsonArr)))
collect(select(df, alias(from_json(df$people, "array<struct<name:string>>"), "arrcol")))
```
prints
```R
arrcol
1 Bob, Alice
```
## How was this patch tested?
Unit tests in `test_sparkSQL.R`.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #17178 from HyukjinKwon/SPARK-19828.
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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.