Re: [I] The query result of `col > x` may be incorrect when there are NaN values in the column `col` [iceberg]

2025-01-15 Thread via GitHub
github-actions[bot] closed issue #9130: The query result of `col > x` may be incorrect when there are NaN values in the column `col` URL: https://github.com/apache/iceberg/issues/9130 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to Git

Re: [I] The query result of `col > x` may be incorrect when there are NaN values in the column `col` [iceberg]

2025-01-15 Thread via GitHub
github-actions[bot] commented on issue #9130: URL: https://github.com/apache/iceberg/issues/9130#issuecomment-2594192084 This issue has been closed because it has not received any activity in the last 14 days since being marked as 'stale' -- This is an automated message from the Apache Gi

Re: [I] The query result of `col > x` may be incorrect when there are NaN values in the column `col` [iceberg]

2023-11-23 Thread via GitHub
zhongyujiang commented on issue #9130: URL: https://github.com/apache/iceberg/issues/9130#issuecomment-1824103082 Agg push down has the same issue: ![image](https://github.com/apache/iceberg/assets/42907416/0f78bc18-a68d-4598-a76c-c499818138d9) -- This is an automated message from

Re: [I] The query result of `col > x` may be incorrect when there are NaN values in the column `col` [iceberg]

2023-11-22 Thread via GitHub
zhongyujiang commented on issue #9130: URL: https://github.com/apache/iceberg/issues/9130#issuecomment-1822694319 Since NaNs are not permitted as lower or upper bounds in Iceberg, should we convert Spark's `col > x` filter to Iceberg's `col > x OR col is NaN` if `col` is `float` or `double`

[I] The query result of `col > x` may be incorrect when there are NaN values in the column `col` [iceberg]

2023-11-22 Thread via GitHub
zhongyujiang opened a new issue, #9130: URL: https://github.com/apache/iceberg/issues/9130 ### Apache Iceberg version 1.4.2 (latest release) ### Query engine Spark ### Please describe the bug 🐞 I found that when there are NaN values in the columns, the resul