Spark Project Catalyst 3.4.0 API < Back

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package root
Definition Classes
root
package org
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root
package apache
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org
package spark
Definition Classes
apache
package sql
Definition Classes
spark
package catalyst
Catalyst is a library for manipulating relational query plans.
Catalyst is a library for manipulating relational query plans. All classes in catalyst are considered an internal API to Spark SQL and are subject to change between minor releases.
Definition Classes
sql
package expressions
A set of classes that can be used to represent trees of relational expressions.
A set of classes that can be used to represent trees of relational expressions. A key goal of the expression library is to hide the details of naming and scoping from developers who want to manipulate trees of relational operators. As such, the library defines a special type of expression, a NamedExpression in addition to the standard collection of expressions.
Standard Expressions
A library of standard expressions (e.g., Add, EqualTo), aggregates (e.g., SUM, COUNT), and other computations (e.g. UDFs). Each expression type is capable of determining its output schema as a function of its children's output schema.
Named Expressions
Some expression are named and thus can be referenced by later operators in the dataflow graph. The two types of named expressions are AttributeReferences and Aliases. AttributeReferences refer to attributes of the input tuple for a given operator and form the leaves of some expression trees. Aliases assign a name to intermediate computations. For example, in the SQL statement SELECT a+b AS c FROM ..., the expressions a and b would be represented by AttributeReferences and c would be represented by an Alias.
During analysis, all named expressions are assigned a globally unique expression id, which can be used for equality comparisons. While the original names are kept around for debugging purposes, they should never be used to check if two attributes refer to the same value, as plan transformations can result in the introduction of naming ambiguity. For example, consider a plan that contains subqueries, both of which are reading from the same table. If an optimization removes the subqueries, scoping information would be destroyed, eliminating the ability to reason about which subquery produced a given attribute.
Evaluation
The result of expressions can be evaluated using the Expression.apply(Row) method.
Definition Classes
catalyst
package aggregate
Definition Classes
expressions
AggregateExpression
AggregateFunction
AggregateMode
AnyValue
ApproxCountDistinctForIntervals
ApproximatePercentile
Average
BitAggregate
BitAndAgg
BitOrAgg
BitXorAgg
BloomFilterAggregate
BoolAnd
BoolOr
CentralMomentAgg
Collect
CollectList
CollectSet
CollectTopK
Complete
Corr
Count
CountIf
CountMinSketchAgg
CovPopulation
CovSample
Covariance
DeclarativeAggregate
Final
First
FirstLast
HistogramNumeric
HyperLogLogPlusPlus
ImperativeAggregate
Kurtosis
Last
Max
MaxBy
MaxMinBy
Median
Min
MinBy
Mode
NoOp
NumericHistogramSerializer
PandasCovar
PandasKurtosis
PandasMode
PandasProduct
PandasSkewness
PandasStddev
PandasVariance
Partial
PartialMerge
PearsonCorrelation
Percentile
PercentileBase
PercentileCont
PercentileDisc
PivotFirst
Product
RegrAvgX
RegrAvgY
RegrCount
RegrIntercept
RegrR2
RegrReplacement
RegrSXX
RegrSXY
RegrSYY
RegrSlope
Skewness
StddevPop
StddevSamp
Sum
TryAverageExpressionBuilder
TrySumExpressionBuilder
TypedAggregateWithHashMapAsBuffer
TypedImperativeAggregate
V2Aggregator
VariancePop
VarianceSamp

org.apache.spark.sql.catalyst.expressions.aggregate

ApproximatePercentile

Companion class ApproximatePercentile

object ApproximatePercentile extends Serializable

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class PercentileDigest extends AnyRef
PercentileDigest is a probabilistic data structure used for approximating percentiles with limited memory.
PercentileDigest is a probabilistic data structure used for approximating percentiles with limited memory. PercentileDigest is backed by QuantileSummaries.
class PercentileDigestSerializer extends AnyRef
Serializer for class PercentileDigest
Serializer for class PercentileDigest
This class is thread safe.

Value Members

final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def ##: Int
Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean
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AnyRef → Any
val DEFAULT_PERCENTILE_ACCURACY: Int
final def asInstanceOf[T0]: T0
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Any
def clone(): AnyRef
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protected[lang]
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@throws(classOf[java.lang.CloneNotSupportedException]) @native()
final def eq(arg0: AnyRef): Boolean
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def equals(arg0: AnyRef): Boolean
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def finalize(): Unit
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protected[lang]
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@throws(classOf[java.lang.Throwable])
final def getClass(): Class[_ <: AnyRef]
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@native()
def hashCode(): Int
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@native()
final def isInstanceOf[T0]: Boolean
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final def ne(arg0: AnyRef): Boolean
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final def notify(): Unit
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@native()
final def notifyAll(): Unit
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@native()
val serializer: PercentileDigestSerializer
final def synchronized[T0](arg0: => T0): T0
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def toString(): String
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final def wait(): Unit
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@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long, arg1: Int): Unit
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final def wait(arg0: Long): Unit
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