Attribute is the Catalyst name for an input column from a child operator.
An AttributeReference has been resolved, meaning we know which input column
in particular it is referring too. An AttributeReference also has a known
DataType. In contrast, before analysis there might still exist
UnresolvedReferences, which are just string identifiers from a parsed query.
An Expression can be more complex (like you suggested, a + b), though
technically just a is also a very simple Expression. The following console
session shows how these types are composed:
$ build/sbt sql/console
import org.apache.spark.SparkContextimport
org.apache.spark.sql.SQLContextimport
org.apache.spark.sql.catalyst.analysis._import
org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.dsl.expressions._import
org.apache.spark.sql.catalyst.dsl.plans._
sc: org.apache.spark.SparkContext = org.apache.spark.SparkContext@5adfe37d
sqlContext: org.apache.spark.sql.SQLContext =
org.apache.spark.sql.SQLContext@20d05227import
sqlContext.implicits._import sqlContext._Welcome to Scala version
2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_45).Type in
expressions to have them evaluated.Type :help for more information.
scala> val unresolvedAttr: UnresolvedAttribute = 'a
unresolvedAttr: org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute = 'a
scala> val relation = LocalRelation('a.int)
relation: org.apache.spark.sql.catalyst.plans.logical.LocalRelation =
LocalRelation [a#0]
scala> val parsedQuery = relation.select(unresolvedAttr)
parsedQuery: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
'Project ['a]
LocalRelation [a#0]
scala> parsedQuery.analyze
res11: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan = Project [a#0]
LocalRelation [a#0]
The #0 after a is a unique identifier (within this JVM) that says where the
data is coming from, even as plans are rearranged due to optimizations.
On Mon, Aug 24, 2015 at 6:13 PM, Todd <bit1...@163.com> wrote:
> There are many such kind of case class or concept such as
> Attribute/AttributeReference/Expression in Spark SQL
>
> I would ask what Attribute/AttributeReference/Expression mean， given a sql
> query like select a,b from c, it a, b are two Attributes? a + b is an
> expression?
> Looks I misunderstand it because Attribute is extending Expression in the
> code,which means Attribute itself is an Expression.
>
>
> Thanks.
>
