[
https://issues.apache.org/jira/browse/SPARK-39173?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yuming Wang updated SPARK-39173:
--------------------------------
Description:
How to reproduce this issue:
{code:scala}
Seq(-1, 1000000000L).foreach { broadcastThreshold =>
withSQLConf(
SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> broadcastThreshold.toString,
SQLConf.ANSI_ENABLED.key -> "true") {
val df = sql(
"""
|SELECT
| item.i_brand_id brand_id,
| avg(ss_ext_sales_price) avg_agg
|FROM store_sales, item
|WHERE store_sales.ss_item_sk = item.i_item_sk
|GROUP BY item.i_brand_id
""".stripMargin)
df.collect()
}
}
{code}
{noformat}
Error message: org.apache.spark.SparkArithmeticException:
[CANNOT_CHANGE_DECIMAL_PRECISION]
Decimal(expanded,999999999999999999999999999999999.28175,38,5}) cannot be
represented as Decimal(38, 6). If necessary set "spark.sql.ansi.enabled" to
false to bypass this error.
Error message: org.apache.spark.SparkArithmeticException: [ARITHMETIC_OVERFLOW]
Overflow in sum of decimals. If necessary set spark.sql.ansi.enabled to false
(except for ANSI interval type) to bypass this error.
{noformat}
was:
How to reproduce this issue:
{code:scala}
Seq(-1, 1000000000L).foreach { broadcastThreshold =>
withSQLConf(
SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> broadcastThreshold.toString,
SQLConf.ANSI_ENABLED.key -> "true") {
val df = sql(
"""
|SELECT
| item.i_brand_id brand_id,
| avg(ss_ext_sales_price) avg_agg
|FROM store_sales, item
|WHERE store_sales.ss_item_sk = item.i_item_sk
|GROUP BY item.i_brand_id
""".stripMargin)
df.collect()
}
}
{code}
{noformat}
Error message: Job aborted due to stage failure: Task 0 in stage 10.0 failed 1
times, most recent failure: Lost task 0.0 in stage 10.0 (TID 9) (localhost
executor driver): org.apache.spark.SparkArithmeticException:
[CANNOT_CHANGE_DECIMAL_PRECISION]
Decimal(expanded,999999999999999999999999999999999.28175,38,5}) cannot be
represented as Decimal(38, 6). If necessary set "spark.sql.ansi.enabled" to
false to bypass this error.
Error message: Job aborted due to stage failure: Task 0 in stage 14.0 failed 1
times, most recent failure: Lost task 0.0 in stage 14.0 (TID 14) (localhost
executor driver): org.apache.spark.SparkArithmeticException:
[ARITHMETIC_OVERFLOW] Overflow in sum of decimals. If necessary set
spark.sql.ansi.enabled to false (except for ANSI interval type) to bypass this
error.
{noformat}
> The error message is different if disable broadcast join
> --------------------------------------------------------
>
> Key: SPARK-39173
> URL: https://issues.apache.org/jira/browse/SPARK-39173
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.4.0
> Reporter: Yuming Wang
> Priority: Major
>
> How to reproduce this issue:
> {code:scala}
> Seq(-1, 1000000000L).foreach { broadcastThreshold =>
> withSQLConf(
> SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> broadcastThreshold.toString,
> SQLConf.ANSI_ENABLED.key -> "true") {
> val df = sql(
> """
> |SELECT
> | item.i_brand_id brand_id,
> | avg(ss_ext_sales_price) avg_agg
> |FROM store_sales, item
> |WHERE store_sales.ss_item_sk = item.i_item_sk
> |GROUP BY item.i_brand_id
> """.stripMargin)
> df.collect()
> }
> }
> {code}
> {noformat}
> Error message: org.apache.spark.SparkArithmeticException:
> [CANNOT_CHANGE_DECIMAL_PRECISION]
> Decimal(expanded,999999999999999999999999999999999.28175,38,5}) cannot be
> represented as Decimal(38, 6). If necessary set "spark.sql.ansi.enabled" to
> false to bypass this error.
> Error message: org.apache.spark.SparkArithmeticException:
> [ARITHMETIC_OVERFLOW] Overflow in sum of decimals. If necessary set
> spark.sql.ansi.enabled to false (except for ANSI interval type) to bypass
> this error.
> {noformat}
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