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Piotr Nowojski commented on FLINK-10257: ---------------------------------------- This is another thing that complicates things even more :/ It would be easier to ignore collation modes if that's possible, for example by saying that we only support one, the one that is easier for us to provide at the moment. [~hequn8128] do you know if calcite currently supports different collation modes? On the other hand, *CHAR literals* (or even regular CHAR columns) with *NO PAD collation mode* can lead to the unexpected/quirky results, like this {{case when}} example. IMO for usability I would vote for either for *VARCHAR literals* or *CHAR literals with PAD SPACE* collation mode for CHARs comparisons. > Incorrect CHAR type support in Flink SQL and Table API > ------------------------------------------------------ > > Key: FLINK-10257 > URL: https://issues.apache.org/jira/browse/FLINK-10257 > Project: Flink > Issue Type: Bug > Components: Table API & SQL > Reporter: Piotr Nowojski > Priority: Critical > > Despite that we officially do not support CHAR type, this type is visible and > accessible for the users. First of all, string literals have default type of > CHAR in SQL. Secondly users can always cast expressions/columns to CHAR. > Problem is that we do not support CHAR correctly. We mishandle it in: > # comparisons and functions > # writing values to sinks > According to SQL standard (and as almost all of the other databases do), CHAR > comparisons should ignore white spaces. On the other hand, functions like > {{CONCAT}} or {{LENGTH}} shouldn't: > [http://troels.arvin.dk/db/rdbms/#data_types-char] . > Currently in In Flink we completely ignore those rules. Sometimes we store > internally CHAR with padded spaces sometimes without. This results with semi > random behaviour with respect to comparisons/functions/writing to sinks. For > example following query: > {code:java} > tEnv.sqlQuery("SELECT CAST(s AS CHAR(10)) FROM > sourceTable").insertInto("targetTable") > env.execute() > {code} > Where `sourceTable` has single {{VARCHAR(10)}} column with values: "Hi", > "Hello", "Hello world", writes to sink not padded strings (correctly), but > following query: > {code:java} > tEnv.sqlQuery("SELECT * FROM (SELECT CAST(s AS CHAR(10)) c FROM sourceTable) > WHERE c = 'Hi'") > .insertInto("targetTable") > env.execute(){code} > Incorrectly filters out all of the results, because {{CAST(s AS CHAR(10))}} > is a NOOP in Flink, while 'Hi' constant handed by Calcite to us will be > padded with 8 spaces. > On the other hand following query produces strings padded with spaces: > {code:java} > tEnv.sqlQuery("SELECT CASE l WHEN 1 THEN 'GERMANY' WHEN 2 THEN 'POLAND' ELSE > 'this should not happen' END FROM sourceTable") > .insertInto("targetTable") > env.execute() > val expected = Seq( > "GERMANY", > "POLAND", > "POLAND").mkString("\n") > org.junit.ComparisonFailure: Different elements in arrays: expected 3 > elements and received 3 > expected: [GERMANY, POLAND, POLAND] > received: [GERMANY , POLAND , POLAND ] > {code} > To make matter even worse, Calcite's constant folding correctly performs > comparisons, while if same comparisons are performed by Flink, they yield > different results. In other words in SQL: > {code:java} > SELECT 'POLAND' = 'POLAND ' > {code} > return true, but same expression performed on columns > {code:java} > SELECT CAST(country as CHAR(10)) = CAST(country_padded as CHAR(10)) FROM > countries{code} > returns false. > To further complicated things, in SQL our string literals have {{CHAR}} type, > while in Table API our literals have String type (effectively {{VARCHAR}}) > making results inconsistent between those two APIs. > > CC [~twalthr] [~fhueske] [~hequn8128] -- This message was sent by Atlassian JIRA (v7.6.3#76005)