spark-instrumented-optimizer/sql
Kent Yao 697083c051 [SPARK-31469][SQL] Make extract interval field ANSI compliance
### What changes were proposed in this pull request?

Currently, we can extract `millennium/century/decade/year/quarter/month/week/day/hour/minute/second(with fractions)//millisecond/microseconds` and `epoch` from interval values

While getting the `millennium/century/decade/year`, it means how many the interval `months` part can be converted to that unit-value. The content of `millennium/century/decade` will overlap `year` and each other.

While getting `month/day` and so on, it means the integral remainder of the previous unit. Here all the units including `year` are individual.

So while extracting `year`, `month`, `day`, `hour`, `minute`, `second`, which are ANSI primary datetime units, the semantic is `extracting`, but others might refer to `transforming`.

While getting epoch we have treat month as 30 days which varies the natural Calendar rules we use.

To avoid ambiguity, I suggest we should only support those extract field defined ANSI with their abbreviations.

### Why are the changes needed?

Extracting `millennium`, `century` etc does not obey the meaning of extracting, and they are not so useful and worth maintaining.

The `extract` is ANSI standard expression and `date_part` is its pg-specific alias function. The current support extract-fields are fully bought from PostgreSQL.

With a look at other systems like Presto/Hive, they don't support those ambiguous fields too.

e.g. Hive 2.2.x also take it from PostgreSQL but without introducing those ambiguous fields https://issues.apache.org/jira/secure/attachment/12828349/HIVE-14579

e.g. presto

```sql
presto> select extract(quater from interval '10-0' year to month);
Query 20200417_094723_00020_m8xq4 failed: line 1:8: Invalid EXTRACT field: quater
select extract(quater from interval '10-0' year to month)

presto> select extract(decade from interval '10-0' year to month);
Query 20200417_094737_00021_m8xq4 failed: line 1:8: Invalid EXTRACT field: decade
select extract(decade from interval '10-0' year to month)

```

### Does this PR introduce any user-facing change?

Yes, as we already have previews versions, this PR will remove support for extracting `millennium/century/decade/quarter/week/millisecond/microseconds` and `epoch` from intervals with `date_part` function

### How was this patch tested?

rm some used tests

Closes #28242 from yaooqinn/SPARK-31469.

Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-04-17 13:59:02 +00:00
..
catalyst [SPARK-31469][SQL] Make extract interval field ANSI compliance 2020-04-17 13:59:02 +00:00
core [SPARK-31469][SQL] Make extract interval field ANSI compliance 2020-04-17 13:59:02 +00:00
hive [SPARK-31425][SQL][CORE] UnsafeKVExternalSorter/VariableLengthRowBasedKeyValueBatch should also respect UnsafeAlignedOffset 2020-04-17 04:48:27 +00:00
hive-thriftserver [SPARK-31291][SQL][TEST][FOLLOWUP] Fix resource loading error in ThriftServerQueryTestSuite 2020-04-11 08:23:59 -07:00
create-docs.sh [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00
gen-sql-api-docs.py [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00
gen-sql-config-docs.py [SPARK-30840][CORE][SQL] Add version property for ConfigEntry and ConfigBuilder 2020-02-22 09:46:42 +09:00
mkdocs.yml [SPARK-30731] Update deprecated Mkdocs option 2020-02-19 17:28:58 +09:00
README.md [SPARK-30510][SQL][DOCS] Publicly document Spark SQL configuration options 2020-02-09 19:20:47 +09:00

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.