2af2da5a4b
### What changes were proposed in this pull request? This patch addresses the case where compact metadata file is read twice in FileStreamSource during restarting query. When restarting the query, there is a case which the query starts from compaction batch, and the batch has source metadata file to read. One case is that the previous query succeeded to read from inputs, but not finalized the batch for various reasons. The patch finds the latest compaction batch when restoring from metadata log, and put entries for the batch into the file entry cache which would avoid reading compact batch file twice. FileStreamSourceLog doesn't know about offset / commit metadata in checkpoint so doesn't know which exactly batch to start from, but in practice, only couple of latest batches are candidates to be started from when restarting query. This patch leverages the fact to skip calculation if possible. ### Why are the changes needed? Spark incurs unnecessary cost on reading the compact metadata file twice on some case, which may not be ignorable when the query has been processed huge number of files so far. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? New UT. Closes #27649 from HeartSaVioR/SPARK-30900. Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com> Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com> |
||
|---|---|---|
| .. | ||
| 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.