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https://issues.apache.org/jira/browse/SPARK-60108?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-60108:
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Labels: pull-request-available (was: )
> JSON CHAR/VARCHAR map keys: exact-width CHAR, no VARCHAR trim
> -------------------------------------------------------------
>
> Key: SPARK-60108
> URL: https://issues.apache.org/jira/browse/SPARK-60108
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core
> Affects Versions: 5.0.0
> Reporter: Serge Rielau
> Priority: Major
> Labels: pull-request-available
>
> When spark.sql.charVarchar.standardSemantics.enabled is true, from_json and
> the JSON datasource already apply CHAR pad and VARCHAR overflow to values in
> JacksonParser (SPARK-59274). JSON map keys are still taken as the raw object
> names.
> Apply length checks to keys in the tokenizer (convertMap /
> parser.currentName). Do not rewrite keys.
> MAP<CHAR(n), _>
> Length < n: error (do not pad).
> Length > n: EXCEED_LIMIT_LENGTH.
> Length = n: keep as-is.
> MAP<VARCHAR(n), _>
> Length > n: EXCEED_LIMIT_LENGTH.
> Otherwise keep as-is. Do not trim trailing spaces.
> Do not call charTypeWriteSideCheck / varcharTypeWriteSideCheck on keys (those
> pad and trim). Add key-specific helpers. CHAR-too-short must not be worded as
> overflow.
> Exact repeated JSON member names stay last-wins. Pad/trim collisions cannot
> occur; do not run mapKeyDedupPolicy for CHAR/VARCHAR key assignment.
> Length failures are parse-mode errors for the whole value. Flag off is
> unchanged. Values, CSV, XML, and TRANSFORM are out of scope.
> Tests: too-short CHAR key; exact-width CHAR key with spaces; CHAR/VARCHAR
> overflow; VARCHAR "ab" vs "ab " remain distinct; exact duplicate names
> last-wins; PERMISSIVE vs FAILFAST; nested maps; from_json and the JSON
> datasource.
> Docs: one migration-guide bullet for JSON CHAR/VARCHAR keys under the flag.
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