5b8444af0d
### What changes were proposed in this pull request? `TPCDSQuerySuite` currently computes plans with empty TPCDS tables, then checks if plans can be generated correctly. But, the generated plans can be different from actual ones because the input tables are empty (e.g., the plans always use broadcast-hash joins, but actual ones use sort-merge joins for larger tables). To mitigate the issue, this PR defines data statistics constants extracted from generated TPCDS data in `TPCDSTableStats`, then injects the statistics via `spark.sessionState.catalog.alterTableStats` when defining TPCDS tables in `TPCDSQuerySuite`. Please see a link below about how to extract the table statistics: - https://gist.github.com/maropu/f553d32c323ee803d39e2f7fa0b5a8c3 For example, the generated plans of TPCDS `q2` are different with/without this fix: ``` ==== w/ this fix: q2 ==== == Physical Plan == * Sort (43) +- Exchange (42) +- * Project (41) +- * SortMergeJoin Inner (40) :- * Sort (28) : +- Exchange (27) : +- * Project (26) : +- * BroadcastHashJoin Inner BuildRight (25) : :- * HashAggregate (19) : : +- Exchange (18) : : +- * HashAggregate (17) : : +- * Project (16) : : +- * BroadcastHashJoin Inner BuildRight (15) : : :- Union (9) : : : :- * Project (4) : : : : +- * Filter (3) : : : : +- * ColumnarToRow (2) : : : : +- Scan parquet default.web_sales (1) : : : +- * Project (8) : : : +- * Filter (7) : : : +- * ColumnarToRow (6) : : : +- Scan parquet default.catalog_sales (5) : : +- BroadcastExchange (14) : : +- * Project (13) : : +- * Filter (12) : : +- * ColumnarToRow (11) : : +- Scan parquet default.date_dim (10) : +- BroadcastExchange (24) : +- * Project (23) : +- * Filter (22) : +- * ColumnarToRow (21) : +- Scan parquet default.date_dim (20) +- * Sort (39) +- Exchange (38) +- * Project (37) +- * BroadcastHashJoin Inner BuildRight (36) :- * HashAggregate (30) : +- ReusedExchange (29) +- BroadcastExchange (35) +- * Project (34) +- * Filter (33) +- * ColumnarToRow (32) +- Scan parquet default.date_dim (31) ==== w/o this fix: q2 ==== == Physical Plan == * Sort (40) +- Exchange (39) +- * Project (38) +- * BroadcastHashJoin Inner BuildRight (37) :- * Project (26) : +- * BroadcastHashJoin Inner BuildRight (25) : :- * HashAggregate (19) : : +- Exchange (18) : : +- * HashAggregate (17) : : +- * Project (16) : : +- * BroadcastHashJoin Inner BuildRight (15) : : :- Union (9) : : : :- * Project (4) : : : : +- * Filter (3) : : : : +- * ColumnarToRow (2) : : : : +- Scan parquet default.web_sales (1) : : : +- * Project (8) : : : +- * Filter (7) : : : +- * ColumnarToRow (6) : : : +- Scan parquet default.catalog_sales (5) : : +- BroadcastExchange (14) : : +- * Project (13) : : +- * Filter (12) : : +- * ColumnarToRow (11) : : +- Scan parquet default.date_dim (10) : +- BroadcastExchange (24) : +- * Project (23) : +- * Filter (22) : +- * ColumnarToRow (21) : +- Scan parquet default.date_dim (20) +- BroadcastExchange (36) +- * Project (35) +- * BroadcastHashJoin Inner BuildRight (34) :- * HashAggregate (28) : +- ReusedExchange (27) +- BroadcastExchange (33) +- * Project (32) +- * Filter (31) +- * ColumnarToRow (30) +- Scan parquet default.date_dim (29) ``` This comes from the cloud-fan comment: https://github.com/apache/spark/pull/29270#issuecomment-666098964 ### Why are the changes needed? For better test coverage. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Existing tests. Closes #29384 from maropu/AddTPCDSTableStats. Authored-by: Takeshi Yamamuro <yamamuro@apache.org> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> |
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| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-api-docs.py | ||
| gen-sql-config-docs.py | ||
| gen-sql-functions-docs.py | ||
| mkdocs.yml | ||
| 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 extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow 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.
Running ./sql/create-docs.sh generates SQL documentation for built-in functions under sql/site, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.