5a482e7209
### What changes were proposed in this pull request?
Change Literal.sql to output CAST('fpValue' AS FLOAT) instead of CAST(fpValue AS FLOAT) as the SQL for a floating point literal.
### Why are the changes needed?
The old version doesn't work for very small floating point numbers; the value will fail to parse if it doesn't fit in a DECIMAL(38).
This doesn't apply to doubles because they have special literal syntax.
### Does this PR introduce any user-facing change?
Not really.
### How was this patch tested?
New unit tests.
Closes #26114 from jose-torres/fpliteral.
Authored-by: Jose Torres <joseph.torres@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-markdown.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.