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[SPARK-26168][SQL] Update the code comments in Expression and Aggregate 

## What changes were proposed in this pull request?
This PR is to improve the code comments to document some common traits and traps about the expression.

## How was this patch tested?
N/A

Closes #23135 from gatorsmile/addcomments.

Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
branch-3.2-sio
gatorsmile 2018-11-26 15:51:28 +08:00 committed by Wenchen Fan
parent 6ab8485da2
commit 6bb60b30fd
4 changed files with 56 additions and 12 deletions
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5
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
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@ -181,8 +181,9 @@ object TypeCoercion {
}
/**
* The method finds a common type for data types that differ only in nullable, containsNull
* and valueContainsNull flags. If the input types are too different, None is returned.
* The method finds a common type for data types that differ only in nullable flags, including
* `nullable`, `containsNull` of [[ArrayType]] and `valueContainsNull` of [[MapType]].
* If the input types are different besides nullable flags, None is returned.
*/
def findCommonTypeDifferentOnlyInNullFlags(t1: DataType, t2: DataType): Option[DataType] = {
if (t1 == t2) {

44
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala
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@ -24,6 +24,7 @@ import org.apache.spark.sql.catalyst.analysis.{TypeCheckResult, TypeCoercion}
import org.apache.spark.sql.catalyst.expressions.aggregate.DeclarativeAggregate
import org.apache.spark.sql.catalyst.expressions.codegen._
import org.apache.spark.sql.catalyst.expressions.codegen.Block._
import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
import org.apache.spark.sql.catalyst.trees.TreeNode
import org.apache.spark.sql.catalyst.util.truncatedString
import org.apache.spark.sql.internal.SQLConf
@ -40,12 +41,28 @@ import org.apache.spark.sql.types._
* "name(arguments...)", the concrete implementation must be a case class whose constructor
* arguments are all Expressions types. See [[Substring]] for an example.
*
* There are a few important traits:
* There are a few important traits or abstract classes:
*
* - [[Nondeterministic]]: an expression that is not deterministic.
* - [[Stateful]]: an expression that contains mutable state. For example, MonotonicallyIncreasingID
* and Rand. A stateful expression is always non-deterministic.
* - [[Unevaluable]]: an expression that is not supposed to be evaluated.
* - [[CodegenFallback]]: an expression that does not have code gen implemented and falls back to
* interpreted mode.
* - [[NullIntolerant]]: an expression that is null intolerant (i.e. any null input will result in
* null output).
* - [[NonSQLExpression]]: a common base trait for the expressions that do not have SQL
* expressions like representation. For example, `ScalaUDF`, `ScalaUDAF`,
* and object `MapObjects` and `Invoke`.
* - [[UserDefinedExpression]]: a common base trait for user-defined functions, including
* UDF/UDAF/UDTF.
* - [[HigherOrderFunction]]: a common base trait for higher order functions that take one or more
* (lambda) functions and applies these to some objects. The function
* produces a number of variables which can be consumed by some lambda
* functions.
* - [[NamedExpression]]: An [[Expression]] that is named.
* - [[TimeZoneAwareExpression]]: A common base trait for time zone aware expressions.
* - [[SubqueryExpression]]: A base interface for expressions that contain a [[LogicalPlan]].
*
* - [[LeafExpression]]: an expression that has no child.
* - [[UnaryExpression]]: an expression that has one child.
@ -54,12 +71,20 @@ import org.apache.spark.sql.types._
* - [[BinaryOperator]]: a special case of [[BinaryExpression]] that requires two children to have
* the same output data type.
*
* A few important traits used for type coercion rules:
* - [[ExpectsInputTypes]]: an expression that has the expected input types. This trait is typically
* used by operator expressions (e.g. [[Add]], [[Subtract]]) to define
* expected input types without any implicit casting.
* - [[ImplicitCastInputTypes]]: an expression that has the expected input types, which can be
* implicitly castable using [[TypeCoercion.ImplicitTypeCasts]].
* - [[ComplexTypeMergingExpression]]: to resolve output types of the complex expressions
* (e.g., [[CaseWhen]]).
*/
abstract class Expression extends TreeNode[Expression] {
/**
* Returns true when an expression is a candidate for static evaluation before the query is
* executed.
* executed. A typical use case: [[org.apache.spark.sql.catalyst.optimizer.ConstantFolding]]
*
* The following conditions are used to determine suitability for constant folding:
* - A [[Coalesce]] is foldable if all of its children are foldable
@ -72,7 +97,8 @@ abstract class Expression extends TreeNode[Expression] {
/**
* Returns true when the current expression always return the same result for fixed inputs from
* children.
* children. The non-deterministic expressions should not change in number and order. They should
* not be evaluated during the query planning.
*
* Note that this means that an expression should be considered as non-deterministic if:
* - it relies on some mutable internal state, or
@ -252,8 +278,9 @@ abstract class Expression extends TreeNode[Expression] {
/**
* An expression that cannot be evaluated. Some expressions don't live past analysis or optimization
* time (e.g. Star). This trait is used by those expressions.
* An expression that cannot be evaluated. These expressions don't live past analysis or
* optimization time (e.g. Star) and should not be evaluated during query planning and
* execution.
*/
trait Unevaluable extends Expression {
@ -724,9 +751,10 @@ abstract class TernaryExpression extends Expression {
}
/**
* A trait resolving nullable, containsNull, valueContainsNull flags of the output date type.
* This logic is usually utilized by expressions combining data from multiple child expressions
* of non-primitive types (e.g. [[CaseWhen]]).
* A trait used for resolving nullable flags, including `nullable`, `containsNull` of [[ArrayType]]
* and `valueContainsNull` of [[MapType]], containsNull, valueContainsNull flags of the output date
* type. This is usually utilized by the expressions (e.g. [[CaseWhen]]) that combine data from
* multiple child expressions of non-primitive types.
*/
trait ComplexTypeMergingExpression extends Expression {

3
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala
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@ -130,6 +130,9 @@ abstract class Attribute extends LeafExpression with NamedExpression with NullIn
* Note that exprId and qualifiers are in a separate parameter list because
* we only pattern match on child and name.
*
* Note that when creating a new Alias, all the [[AttributeReference]] that refer to
* the original alias should be updated to the new one.
*
* @param child The computation being performed
* @param name The name to be associated with the result of computing [[child]].
* @param exprId A globally unique id used to check if an [[AttributeReference]] refers to this

16
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
View File

@ -17,11 +17,11 @@
package org.apache.spark.sql.catalyst.plans.logical
import org.apache.spark.sql.catalyst.{AliasIdentifier}
import org.apache.spark.sql.catalyst.AliasIdentifier
import org.apache.spark.sql.catalyst.analysis.{MultiInstanceRelation, NamedRelation}
import org.apache.spark.sql.catalyst.catalog.{CatalogStorageFormat, CatalogTable}
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, AggregateFunction}
import org.apache.spark.sql.catalyst.plans._
import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, Partitioning, RangePartitioning, RoundRobinPartitioning}
import org.apache.spark.sql.catalyst.util.truncatedString
@ -575,6 +575,18 @@ case class Range(
}
}
/**
* This is a Group by operator with the aggregate functions and projections.
*
* @param groupingExpressions expressions for grouping keys
* @param aggregateExpressions expressions for a project list, which could contain
* [[AggregateFunction]]s.
*
* Note: Currently, aggregateExpressions is the project list of this Group by operator. Before
* separating projection from grouping and aggregate, we should avoid expression-level optimization
* on aggregateExpressions, which could reference an expression in groupingExpressions.
* For example, see the rule [[org.apache.spark.sql.catalyst.optimizer.SimplifyExtractValueOps]]
*/
case class Aggregate(
groupingExpressions: Seq[Expression],
aggregateExpressions: Seq[NamedExpression],