[Bug]: Beam SQL Parquet tables fail on TIME columns: Unhandled logical type beam:logical_type:time:v1

未关闭
  • 哪里不对？
#40,994 1 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看

维护者通常 1 天内回复

还没有人认领这个 Issue。

评估

难度
4/5
预计耗时
3-5 天
新手友好度
48/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
活跃
技术栈
java, sql
领域
backend, databases

调研方向

Start with AvroUtils.getFieldSchema and genericFromBeamField, where the issue identifies the missing TIME identifier handling, and compare them with the DATE conversion paths. Read the Beam SQL TIME mapping in CalciteUtils and inspect the Avro time-millis/time-micros conversions. Add a JUnit regression test under sdks/java/extensions/sql using the DirectRunner repro; done means TIME values can be written to and read back from a Parquet table. The Avro time unit choice needs maintainer guidance.

由索引模型根据 Issue 内容生成。

描述

awaiting triage bug java P2
What happened?

A Beam SQL Parquet table (CREATE EXTERNAL TABLE ... TYPE parquet) with a TIME column can't be written. On master (b0c68c4a4f7), the INSERT fails with:

java.lang.RuntimeException: Unhandled logical type beam:logical_type:time:v1

Minimal repro, run as a JUnit test in sdks/java/extensions/sql with the DirectRunner (p is a TestPipeline):

BeamSqlEnv env = BeamSqlEnv.inMemory(new ParquetTableProvider());
env.executeDdl("CREATE EXTERNAL TABLE t (c TIME) TYPE parquet LOCATION '/tmp/time-table/'");
BeamSqlRelUtils.toPCollection(p, env.parseQuery("INSERT INTO t VALUES (TIME '12:34:56')"));
p.run().waitUntilFinish(); // RuntimeException: Unhandled logical type beam:logical_type:time:v1

Calling AvroUtils.toAvroSchema on the table's schema, which is what ParquetTable does (L60, L69, L111), throws the same exception.

Cause. The two sides use different identifiers for TIME:

  • Beam SQL maps TIME to FieldType.logicalType(SqlTypes.TIME), whose identifier is beam:logical_type:time:v1 (CalciteUtils L114).
  • AvroUtils.getFieldSchema only recognizes the legacy "TIME" identifier (L1224). Every other identifier falls through to the Unhandled logical type exception (L1242).
  • genericFromBeamField has the same gap (L1389, L1406).

DATE does handle both identifiers: "DATE".equals(identifier) || SqlTypes.DATE.getIdentifier().equals(identifier) (L1220). That's why DATE columns work and TIME columns don't.

Expected: TIME columns can be written and read back. The CREATE EXTERNAL TABLE docs list DATE, TIME, TIMESTAMP as supported Parquet types.

A fix probably needs a design call. Should SqlTypes.TIME (a java.time.LocalTime) map to Avro time-micros (long) or time-millis (int)? Reading the column back also has to convert to LocalTime, and the time-millis/time-micros branches of the Avro-to-Beam conversion currently return the raw int/long. I'm happy to send a fix once a maintainer confirms which mapping they'd like.

For reference, here is what AvroUtils.toAvroSchema produces today for each type, from a temporary test that runs CREATE EXTERNAL TABLE ... TYPE parquet for each column type:

Beam SQL type Beam field type Avro type
TINYINT, SMALLINT, INTEGER BYTE, INT16, INT32 int
BIGINT INT64 long
FLOAT FLOAT float
DOUBLE DOUBLE double
DECIMAL DECIMAL bytes (decimal)
BOOLEAN BOOLEAN boolean
DATE SqlTypes.DATE int (date)
TIME SqlTypes.TIME exception
TIMESTAMP DATETIME long (timestamp-millis)
CHAR, VARCHAR STRING string
BINARY, VARBINARY BYTES bytes

Several rows of the docs' Parquet type table don't match this: the int types, FLOAT, DATE and TIME. I'll file that docs correction separately.

Issue Priority

Priority: 2 (default / most bugs should be filed as P2)

Issue Components
  • Component: Python SDK
  • Component: Java SDK
  • Component: Go SDK
  • Component: Typescript SDK
  • Component: IO connector
  • Component: Beam YAML
  • Component: Beam examples
  • Component: Beam playground
  • Component: Beam katas
  • Component: Website
  • Component: Infrastructure
  • Component: Spark Runner
  • Component: Flink Runner
  • Component: Prism Runner
  • Component: Hazelcast Jet Runner
  • Component: Google Cloud Dataflow Runner
主要语言
Java
星标
8.7k
派生
4.8k
平均合并
2 天 12 小时
30 天内合并 PR
371

环境准备

从这里开始

  1. 先读完整个 Issue，再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库，在一个分支上完成修改。
  4. 提交 Pull Request，并在描述里引用这个 Issue 编号。

apache/beam 的其他 Issue

查看 apache/beam 的全部 Issue

相似的 Issue

更多 Java Issue

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。