7b7f16f2a7
## What changes were proposed in this pull request? Current SQL parser's error message for hyphen-connected identifiers without surrounding backquotes(e.g. hyphen-table) is confusing for end users. A possible approach to tackle this is to explicitly capture these wrong usages in the SQL parser. In this way, the end users can fix these errors more quickly. For example, for a simple query such as `SELECT * FROM test-table`, the original error message is ``` Error in SQL statement: ParseException: mismatched input '-' expecting <EOF>(line 1, pos 18) ``` which can be confusing in a large query. After the fix, the error message is: ``` Error in query: Possibly unquoted identifier test-table detected. Please consider quoting it with back-quotes as `test-table`(line 1, pos 14) == SQL == SELECT * FROM test-table --------------^^^ ``` which is easier for end users to identify the issue and fix. We safely augmented the current grammar rule to explicitly capture these error cases. The error handling logic is implemented in the SQL parsing listener `PostProcessor`. However, note that for cases such as `a - my-func(b)`, the parser can't actually tell whether this should be ``a -`my-func`(b) `` or `a - my - func(b)`. Therefore for these cases, we leave the parser as is. Also, in this patch we only provide better error messages for character-only identifiers. ## How was this patch tested? Adding new unit tests. Closes #24749 from yeshengm/hyphen-ident. Authored-by: Yesheng Ma <kimi.ysma@gmail.com> Signed-off-by: gatorsmile <gatorsmile@gmail.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 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 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.