bschoening commented on code in PR #3780:
URL: https://github.com/apache/cassandra/pull/3780#discussion_r1907523207
##########
pylib/cqlshlib/cql3handling.py:
##########
@@ -756,13 +758,35 @@ def working_on_keyspace(ctxt):
<selector> ::= [colname]=<cident> ( "[" ( <term> ( ".." <term> "]" )? | <term>
".." ) )?
| <udtSubfieldSelection>
| "WRITETIME" "(" [colname]=<cident> ")"
- | "MAXWRITETIME" "(" [colname]=<cident> ")"
+ | "MAX_WRITETIME" "(" [colname]=<cident> ")"
+ | "MIN_WRITETIME" "(" [colname]=<cident> ")"
| "TTL" "(" [colname]=<cident> ")"
- | "COUNT" "(" star=( "*" | "1" ) ")"
+ | <aggregateMathFunction>
+ | <scalarMathFunction>
+ | "TO_DATE" "(" [colname]=<cident> ")"
+ | "TO_TIMESTAMP" "(" [colname]=<cident> ")"
+ | "TO_UNIX_TIMESTAMP" "(" [colname]=<cident> ")"
+ | "TOKEN" "(" [colname]=<cident> ")"
+ | "MAP_KEYS" "(" [colname]=<cident> ")"
+ | "MAP_VALUES" "(" [colname]=<cident> ")"
+ | "MIN_TIMEUUID" "(" [colname]=<cident> ")"
+ | "MAX_TIMEUUID" "(" [colname]=<cident> ")"
| "CAST" "(" <selector> "AS" <storageType> ")"
+ | "COLLECTION_AVG" "(" [colname]=<cident> ")"
+ | "COLLECTION_COUNT" "(" [colname]=<cident> ")"
+ | "COLLECTION_MIN" "(" [colname]=<cident> ")"
+ | "COLLECTION_MAX" "(" [colname]=<cident> ")"
+ | "COLLECTION_SUM" "(" [colname]=<cident> ")"
+ | "MASK_NULL" "(" [colname]=<cident> ")"
+ | "MASK_DEFAULT" "(" [colname]=<cident> ")"
+ | "MASK_REPLACE" "(" [colname]=<cident> "," <term> ")"
+ | "MASK_HASH" "(" [colname]=<cident> ")"
+ | "MASK_INNER" "(" [colname]=<cident> ")"
+ | "MASK_OUTER" "(" [colname]=<cident> ")"
Review Comment:
@bbotella Thanks for your reviewing this. The tipping point for grouping
aggregate and scalar math functions was that they have different names (avg,
max, sum), so it nicely grouped them together. The mask_ and collection_ have
a shared prefix. There isn't any reuse of the aggregateMathFunction or
scalarMathFunction groups, so this functions more as documentation. I don't
feel particularly strongly either way though.
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