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Shankar Kandaswamy commented on SPARK-20555: -------------------------------------------- [~gfeher] May i know if first issue has been resolved? "1. DECIMAL(1) becomes BooleanType In Orcale, a DECIMAL(1) can have values from -9 to 9." I am using the spark 2.2.0 but still i am getting Boolean "false" when source is having numeric(1) as 0. I want it as 0 without customschema Could you please advise? > Incorrect handling of Oracle's decimal types via JDBC > ----------------------------------------------------- > > Key: SPARK-20555 > URL: https://issues.apache.org/jira/browse/SPARK-20555 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.1.0 > Reporter: Gabor Feher > Assignee: Gabor Feher > Fix For: 2.1.2, 2.2.0 > > > When querying an Oracle database, Spark maps some Oracle numeric data types > to incorrect Catalyst data types: > 1. DECIMAL(1) becomes BooleanType > In Orcale, a DECIMAL(1) can have values from -9 to 9. > In Spark now, values larger than 1 become the boolean value true. > 2. DECIMAL(3,2) becomes IntegerType > In Oracle, a DECIMAL(2) can have values like 1.23 > In Spark now, digits after the decimal point are dropped. > 3. DECIMAL(10) becomes IntegerType > In Oracle, a DECIMAL(10) can have the value 9999999999 (ten nines), which is > more than 2^31 > Spark throws an exception: "java.sql.SQLException: Numeric Overflow" > I think the best solution is to always keep Oracle's decimal types. (In > theory we could introduce a FloatType in some case of #2, and fix #3 by only > introducing IntegerType for DECIMAL(9). But in my opinion, that would end up > complicated and error-prone.) > Note: I think the above problems were introduced as part of > https://github.com/apache/spark/pull/14377 > The main purpose of that PR seems to be converting Spark types to correct > Oracle types, and that part seems good to me. But it also adds the inverse > conversions. As it turns out in the above examples, that is not possible. -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org