Hi
1.System makes MDK index for dimensions(string columns as dimensions, numeric
columns as measures) , so you have to specify at least one dimension(string
column) for building MDK index.
2.You can set numeric column with DICTIONARY_INCLUDE or DICTIONARY_EXCLUDE to
build MDK index.
For case2, you can change script like :
carbon.sql("create table if not exists test(a integer, b integer, c integer)
STORED BY 'carbondata' TBLPROPERTIES ('DICTIONARY_INCLUDE'='a')");
Regards
Liang
2017-03-23 18:39 GMT+05:30 Jin Zhou <eman1...@163.com>:
> Exception info:
> scala> carbon.sql("create table if not exists test(a integer, b integer, c
> integer) STORED BY 'carbondata'");
> org.apache.carbondata.spark.exception.MalformedCarbonCommandException:
> Table
> default.test can not be created without key columns. Please use
> DICTIONARY_INCLUDE or DICTIONARY_EXCLUDE to set at least one key column if
> all specified columns are numeric types
> at
> org.apache.spark.sql.catalyst.CarbonDDLSqlParser.prepareTableModel(
> CarbonDDLSqlParser.scala:240)
> at
> org.apache.spark.sql.parser.CarbonSqlAstBuilder.visitCreateTable(
> CarbonSparkSqlParser.scala:162)
> at
> org.apache.spark.sql.parser.CarbonSqlAstBuilder.visitCreateTable(
> CarbonSparkSqlParser.scala:60)
> at
> org.apache.spark.sql.catalyst.parser.SqlBaseParser$
> CreateTableContext.accept(SqlBaseParser.java:503)
> at
> org.antlr.v4.runtime.tree.AbstractParseTreeVisitor.visit(
> AbstractParseTreeVisitor.java:42)
> at
> org.apache.spark.sql.catalyst.parser.AstBuilder$$anonfun$
> visitSingleStatement$1.apply(AstBuilder.scala:66)
> at
> org.apache.spark.sql.catalyst.parser.AstBuilder$$anonfun$
> visitSingleStatement$1.apply(AstBuilder.scala:66)
> at
> org.apache.spark.sql.catalyst.parser.ParserUtils$.
> withOrigin(ParserUtils.scala:93)
> at
> org.apache.spark.sql.catalyst.parser.AstBuilder.visitSingleStatement(
> AstBuilder.scala:65)
> at
> org.apache.spark.sql.catalyst.parser.AbstractSqlParser$$
> anonfun$parsePlan$1.apply(ParseDriver.scala:54)
> at
> org.apache.spark.sql.catalyst.parser.AbstractSqlParser$$
> anonfun$parsePlan$1.apply(ParseDriver.scala:53)
> at
> org.apache.spark.sql.catalyst.parser.AbstractSqlParser.
> parse(ParseDriver.scala:82)
> at
> org.apache.spark.sql.parser.CarbonSparkSqlParser.parse(
> CarbonSparkSqlParser.scala:56)
> at
> org.apache.spark.sql.catalyst.parser.AbstractSqlParser.
> parsePlan(ParseDriver.scala:53)
> at
> org.apache.spark.sql.parser.CarbonSparkSqlParser.parsePlan(
> CarbonSparkSqlParser.scala:46)
> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)
> ... 50 elided
>
> I didn't notice “if all specified columns are numeric types” in exception
> info. So I did more tests and found the issue only occurs when all columns
> are numeric types.
>
> Below are cases I tested:
> case 1：
> carbon.sql("create table if not exists test(a string, b string, c string)
> STORED BY 'carbondata' 'DICTIONARY_EXCLUDE'='a,b,c' ");
> ====> ok, no dictionary column
>
> case 2：
> carbon.sql("create table if not exists test(a integer, b integer, c
> integer)
> STORED BY 'carbondata'");
> ====> fail
>
> case 3:
> carbon.sql("create tale if not exists test(a integer, b integer, c integer)
> STORED BY 'carbondata' TBLPROPERTIES ('DICTIONARY_INCLUDE'='a')");
> ====> ok, at least one dictionary column
>
> One little problem about case 2 is that there are no proper dictionary
> column when all columns have high cardinality.
>
>
>
>
> --
> View this message in context: http://apache-carbondata-
> mailing-list-archive.1130556.n5.nabble.com/Questions-about-
> dictionary-encoded-column-and-MDK-tp9457p9484.html
> Sent from the Apache CarbonData Mailing List archive mailing list archive
> at Nabble.com.
>
--
Regards
Liang
