[Java] Spark job fails due to arrow buf limitation
- 主要語言
- Java
- 星號
- 94
- 分支
- 152
- 平均合併
- 3 天 16 小時
- 30 天內合併 PR
- 11
描述
Hello,
Groupby + applyinPandas results in following error. We need some parameter to tune buffer size.
```java
Caused by: java.lang.IndexOutOfBoundsException: index: 0, length: 1073741824 (expected: range(0, 0)) at io.netty.buffer.ArrowBuf.checkIndex(ArrowBuf.java:716) at io.netty.buffer.ArrowBuf.setBytes(ArrowBuf.java:954) at org.apache.arrow.vector.BaseVariableWidthVector.reallocDataBuffer(BaseVariableWidthVector.java:508) at org.apache.arrow.vector.BaseVariableWidthVector.handleSafe(BaseVariableWidthVector.java:1239) at org.apache.arrow.vector.BaseVariableWidthVector.setSafe(BaseVariableWidthVector.java:1066) at org.apache.spark.sql.execution.arrow.StringWriter.setValue(ArrowWriter.scala:287) at org.apache.spark.sql.execution.arrow.ArrowFieldWriter.write(ArrowWriter.scala:151) at org.apache.spark.sql.execution.arrow.ArrowWriter.write(ArrowWriter.scala:105) at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.$anonfun$writeIteratorToStream$1(ArrowPythonRunner.scala:100) at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1581) at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.writeIteratorToStream(ArrowPythonRunner.scala:122) at org.apache.spark.api.python.BasePythonRunner$WriterThread.$anonfun$run$1(PythonRunner.scala:478) at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:2146) at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:270)
```
**Reporter**: [Shubham Chhabra](https://issues.apache.org/jira/browse/ARROW-15983)
**Note**: *This issue was originally created as [ARROW-15983](https://issues.apache.org/jira/browse/ARROW-15983). Please see the [migration documentation](https://github.com/apache/arrow/issues/14542) for further details.*
貢獻指南
研究方向
追蹤指向 ArrowBuf.java、BaseVariableWidthVector、Spark 的 ArrowWriter.scala 和 ArrowPythonRunner.scala;先重現 groupby + applyInPandas 案例,並追蹤 buffer 邊界。完成表示已透過所要求的可調整 buffer 行為處理回報的失敗,並為此路徑補上 coverage。
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- java, scala, spark
- 領域
- data-engineering
- Issue 類型
- 缺陷
- 難度
- 4/5
- 預估耗時
- 3-5 天
- 活躍度
- 停滯
- 描述清晰度
- 需要釐清
- 新手友好度
- 25/100