panbingkun commented on code in PR #45834:
URL: https://github.com/apache/spark/pull/45834#discussion_r1550609240
##########
common/utils/src/main/scala/org/apache/spark/internal/LogKey.scala:
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@@ -21,17 +21,56 @@ package org.apache.spark.internal
* All structured logging keys should be defined here for standardization.
*/
object LogKey extends Enumeration {
- val APPLICATION_ID = Value
+ val EXECUTOR_ID = Value
Review Comment:
I originally planned to categorize by `category` first, and then sort it in
`alphabetical order` for the second level.
Let me give an example:
```
APPLICATION-ID
K8S1ID
MEMOSL_ID
MAX_SIZE
MIN_SIZE
```
If we only sort by `alphabetically`, we will get:
```
APPLICATION_ID
MAX_SIZE
MEMOSL_ID
MIN_SIZE
K8S_ID
```
It's a bit weird for me to see `MEMOS_ID` between `MAX_SIZE` and `MIN-SIZE`.
If we first classify by `category` at the first level and then by
`alphabetically ` at the second level, we will obtain
```
# ID
APPLICATION_ID
MEMOSL_ID
K8S_ID
# SHUFFLE Value
MAX_SIZE
MIN_SIZE
```
Just like:
https://github.com/apache/spark/blob/7dec5eb14644aee6c0562bad1d14421d9fa07f17/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala#L602-L610
I think as our log migration work progresses, this class will become more
and more large. If only sort by `alphabetically` , it is not sure whether
developers and the final log searcher can quickly find the `LogKey` they want.
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