Implement Spark-compatible `regexp_count`
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Valutazione
- Difficoltà
- 4/5
- Tempo stimato
- 3-5 giorni
- Idoneità per principianti
- 25/100
Direzione di ricerca
Start by reading the existing string functions under crates/spark/src/function/string/, especially the regexp_extract_all implementation, since regexp_count must share its matching core rather than wrap DataFusion's regexpcount.rs. The issue is explicit that the Java-regex compatibility helper proposed for rlike does not exist yet, so confirm with a maintainer whether this work is blocked on it before writing anything. Done means a new regexp_count function with #[user_doc], plus crates/sqllogictest/test_files/string/regexp_count.slt covering the listed edge cases (NULLs, empty pattern, non-overlapping matches, invalid pattern, collation).
Scritto dal modello di indicizzazione a partire dal testo della issue.
Descrizione
Part of #174 and apache/datafusion-comet#7300.
What the function does
regexp_count(str, regexp) returns the number of times the Java regular expression regexp matches in str. It is RuntimeReplaceable: the analyzer rewrites it to size(regexp_extract_all(str, regexp, 0), legacySizeOfNull = false), so it counts the matches found by repeated Matcher.find(). Available since 3.4.0.
Both arguments are implicitly cast to STRING. Result is INT. NULL if either argument is NULL. There are no start or flags arguments.
Examples
SELECT regexp_count('Steven Jones and Stephen Smith are the best players', 'Ste(v|ph)en');
-- 2
SELECT regexp_count('abcdefghijklmnopqrstuvwxyz', '[a-z]{3}');
-- 8
SELECT regexp_count('1a 2b 14m', '\\d+');
-- 3
SELECT regexp_count('the fox', 'FOX');
-- 0
SELECT regexp_count('the fox', '(?i)FOX');
-- 1
SELECT regexp_count('passwd7 plain A1234 a1234', '(?=[^ ]*[a-z])(?=[^ ]*[0-9])[^ ]+');
-- 2
SELECT regexp_count(null, 'abc');
-- NULL
Edge cases to test
- NULL
stror NULLregexp, literal and column: NULL. - Matches are non-overlapping:
'[a-z]{3}'over 26 letters is 8. - Empty pattern:
regexp_count('abc', '')is 4 (one empty match at each of the 4 positions).regexp_count('', '')is 1. - Empty matches after a non-empty match: Java counts them, the
regexcrate does not (itstestdata/empty.tomlgives 3 matches forb|onabc; Java finds 4).regexp_count('1a 2b 14m', '(\\d+)?')is 9 in Spark (the same matches as theregexp_extract_allgolden result["1","","","2","","","14","",""]). - Invalid pattern:
INVALID_PARAMETER_VALUE.PATTERN. Because of the rewrite, thefunctionNamein the error is`regexp_extract_all`, notregexp_count. - Column patterns (different per row).
spark.sql.parser.escapedStringLiterals(default false) only changes how the SQL literal reaches the function. In.slt, DataFusion keeps backslashes literal.- Java vs Rust divergences to decline or test: lookaround (the
passwd7example above needs it), backreferences, atomic groups, possessive quantifiers; ASCII\d\w\sin Java vs Unicode in Rust (regexp_count('1\u0663', '\\d'), U+0663 ARABIC-INDIC DIGIT THREE, is 1 in Spark);.excludes\r,\u0085,\u2028,\u2029in Java;$matches before a final line terminator in Java (regexp_count('a\n', 'a$')is 1);(?i)ASCII-only in Java (U+212A KELVIN SIGN does not match(?i)k); inline flag lettersU,u,d; Java-only\Q..\E,\h,\R,\Z; Rust-only(?P<n>),\<,[[:alpha:]]. UTF8_LCASEcollation (4.0+) counts case-insensitively.
Differences across Spark versions
- 4.0: collation-aware input types. Otherwise none found (3.4.0 through 4.2.0).
Implementation notes
- Spark:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/regexpExpressions.scala,RegExpCount(replacement usesRegExpExtractAllandSize). - Because of the rewrite, Spark plans (and Comet) never contain
RegExpCount; engines that translate Spark plans will seesize(regexp_extract_all(...)). A directregexp_countUDF is still useful for SQL users ofdatafusion-sparkand should share the matching core withregexp_extract_all. - DataFusion core
regexp_count(str, regexp[, start[, flags]])(datafusion/functions/src/regex/regexpcount.rs) returns BIGINT, acceptsstartandflags, and uses Rust regex syntax and Rust empty-match iteration. Do not wrap it unchanged. - Use the shared Java-regex compatibility helper proposed for
rlike(verified subset, decline otherwise, decided at planning time for literal patterns). - Belongs in
crates/spark/src/function/string/. Addcrates/sqllogictest/test_files/string/regexp_count.sltand document with#[user_doc].
This issue was generated by an LLM (Claude) from the Apache Spark source code and tests. Examples come from Spark's ExpressionDescription examples, test suites and .sql.out golden files, but please verify them against Spark before relying on them.
- Lingua principale
- Rust
- Stelle
- 7
- Fork
- 15
- Merge medio
- 16h 43m
- PR unite (30g)
- 26
Preparare l'ambiente
- Nessun Dockerfile né file Docker Compose
- Nessun modello di pull request
- Leggi la guida per i contributori
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- Leggi tutta la issue e poi la guida ai contributi del progetto.
- Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
- Fai un fork del repository e lavora su un branch.
- Apri una pull request che faccia riferimento al numero della issue.
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