Package org.apache.spark.sql

Class Column

Object

org.apache.spark.sql.Column

All Implemented Interfaces:

org.apache.spark.internal.Logging

Direct Known Subclasses:

ColumnName, TypedColumn

public class Column
extends Object
implements org.apache.spark.internal.Logging

A column that will be computed based on the data in a DataFrame.

A new column can be constructed based on the input columns present in a DataFrame:

   df("columnName")            // On a specific `df` DataFrame.
   col("columnName")           // A generic column not yet associated with a DataFrame.
   col("columnName.field")     // Extracting a struct field
   col("`a.column.with.dots`") // Escape `.` in column names.
   $"columnName"               // Scala short hand for a named column.
 

Column objects can be composed to form complex expressions:

   $"a" + 1
   $"a" === $"b"
 

Since:

1.3.0

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Constructor Summary

Constructors

Constructor	Description
Column(String name)
Column(org.apache.spark.sql.internal.ColumnNode node)

Method Summary

Modifier and Type	Method	Description
Column	alias(String alias)	Gives the column an alias.
Column	and(Column other)	Boolean AND.
Column	apply(Object extraction)	Extracts a value or values from a complex type.
Column	as(String alias)	Gives the column an alias.
Column	as(String[] aliases)	Assigns the given aliases to the results of a table generating function.
Column	as(String alias, Metadata metadata)	Gives the column an alias with metadata.
<U> TypedColumn<Object,U>	as(Encoder<U> evidence$1)	Provides a type hint about the expected return value of this column.
Column	as(scala.collection.immutable.Seq<String> aliases)	(Scala-specific) Assigns the given aliases to the results of a table generating function.
Column	as(scala.Symbol alias)	Gives the column an alias.
Column	asc()	Returns a sort expression based on ascending order of the column.
Column	asc_nulls_first()	Returns a sort expression based on ascending order of the column, and null values return before non-null values.
Column	asc_nulls_last()	Returns a sort expression based on ascending order of the column, and null values appear after non-null values.
Column	between(Object lowerBound, Object upperBound)	True if the current column is between the lower bound and upper bound, inclusive.
Column	bitwiseAND(Object other)	Compute bitwise AND of this expression with another expression.
Column	bitwiseOR(Object other)	Compute bitwise OR of this expression with another expression.
Column	bitwiseXOR(Object other)	Compute bitwise XOR of this expression with another expression.
Column	cast(String to)	Casts the column to a different data type, using the canonical string representation of the type.
Column	cast(DataType to)	Casts the column to a different data type.
Column	contains(Object other)	Contains the other element.
Column	desc()	Returns a sort expression based on the descending order of the column.
Column	desc_nulls_first()	Returns a sort expression based on the descending order of the column, and null values appear before non-null values.
Column	desc_nulls_last()	Returns a sort expression based on the descending order of the column, and null values appear after non-null values.
Column	divide(Object other)	Division this expression by another expression.
Column	dropFields(scala.collection.immutable.Seq<String> fieldNames)	An expression that drops fields in StructType by name.
Column	endsWith(String literal)	String ends with another string literal.
Column	endsWith(Column other)	String ends with.
Column	eqNullSafe(Object other)	Equality test that is safe for null values.
boolean	equals(Object that)
Column	equalTo(Object other)	Equality test.
void	explain(boolean extended)	Prints the expression to the console for debugging purposes.
Column	geq(Object other)	Greater than or equal to an expression.
Column	getField(String fieldName)	An expression that gets a field by name in a StructType.
Column	getItem(Object key)	An expression that gets an item at position ordinal out of an array, or gets a value by key key in a MapType.
Column	gt(Object other)	Greater than.
int	hashCode()
Column	ilike(String literal)	SQL ILIKE expression (case insensitive LIKE).
Column	isin(Object... list)	A boolean expression that is evaluated to true if the value of this expression is contained by the evaluated values of the arguments.
Column	isin(scala.collection.immutable.Seq<Object> list)	A boolean expression that is evaluated to true if the value of this expression is contained by the evaluated values of the arguments.
Column	isInCollection(Iterable<?> values)	A boolean expression that is evaluated to true if the value of this expression is contained by the provided collection.
Column	isInCollection(scala.collection.Iterable<?> values)	A boolean expression that is evaluated to true if the value of this expression is contained by the provided collection.
Column	isNaN()	True if the current expression is NaN.
Column	isNotNull()	True if the current expression is NOT null.
Column	isNull()	True if the current expression is null.
Column	leq(Object other)	Less than or equal to.
Column	like(String literal)	SQL like expression.
Column	lt(Object other)	Less than.
Column	minus(Object other)	Subtraction.
Column	mod(Object other)	Modulo (a.k.a.
Column	multiply(Object other)	Multiplication of this expression and another expression.
Column	name(String alias)	Gives the column a name (alias).
org.apache.spark.sql.internal.ColumnNode	node()
Column	notEqual(Object other)	Inequality test.
Column	or(Column other)	Boolean OR.
Column	otherwise(Object value)	Evaluates a list of conditions and returns one of multiple possible result expressions.
Column	over()	Defines an empty analytic clause.
Column	over(WindowSpec window)	Defines a windowing column.
Column	plus(Object other)	Sum of this expression and another expression.
Column	rlike(String literal)	SQL RLIKE expression (LIKE with Regex).
Column	startsWith(String literal)	String starts with another string literal.
Column	startsWith(Column other)	String starts with.
Column	substr(int startPos, int len)	An expression that returns a substring.
Column	substr(Column startPos, Column len)	An expression that returns a substring.
String	toString()
Column	try_cast(String to)	Casts the column to a different data type and the result is null on failure.
Column	try_cast(DataType to)	Casts the column to a different data type and the result is null on failure.
Column	when(Column condition, Object value)	Evaluates a list of conditions and returns one of multiple possible result expressions.
Column	withField(String fieldName, Column col)	An expression that adds/replaces field in StructType by name.

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.internal.Logging

initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext

Constructor Details

Column

public Column(org.apache.spark.sql.internal.ColumnNode node)

Column

public Column(String name)

Method Details

isin

public Column isin(Object... list)

A boolean expression that is evaluated to true if the value of this expression is contained by the evaluated values of the arguments.

Note: Since the type of the elements in the list are inferred only during the run time, the elements will be "up-casted" to the most common type for comparison. For eg: 1) In the case of "Int vs String", the "Int" will be up-casted to "String" and the comparison will look like "String vs String". 2) In the case of "Float vs Double", the "Float" will be up-casted to "Double" and the comparison will look like "Double vs Double"

Parameters:

list - (undocumented)

Returns:

(undocumented)

Since:

1.5.0

node

public org.apache.spark.sql.internal.ColumnNode node()

toString

public String toString()

Overrides:

toString in class Object

equals

public boolean equals(Object that)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

as

public <U> TypedColumn<Object,U> as(Encoder<U> evidence$1)

Provides a type hint about the expected return value of this column. This information can be used by operations such as select on a Dataset to automatically convert the results into the correct JVM types.

Parameters:

evidence$1 - (undocumented)

Returns:

(undocumented)

Since:

1.6.0

apply

public Column apply(Object extraction)

Extracts a value or values from a complex type. The following types of extraction are supported:

• Given an Array, an integer ordinal can be used to retrieve a single value.
• Given a Map, a key of the correct type can be used to retrieve an individual value.
• Given a Struct, a string fieldName can be used to extract that field.
• Given an Array of Structs, a string fieldName can be used to extract filed of every struct in that array, and return an Array of fields.

Parameters:

extraction - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

equalTo

public Column equalTo(Object other)

Equality test.

   // Scala:
   df.filter( df("colA") === df("colB") )

   // Java
   import static org.apache.spark.sql.functions.*;
   df.filter( col("colA").equalTo(col("colB")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

notEqual

public Column notEqual(Object other)

Inequality test.

   // Scala:
   df.select( df("colA") !== df("colB") )
   df.select( !(df("colA") === df("colB")) )

   // Java:
   import static org.apache.spark.sql.functions.*;
   df.filter( col("colA").notEqual(col("colB")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

gt

public Column gt(Object other)

Greater than.

   // Scala: The following selects people older than 21.
   people.select( people("age") > lit(21) )

   // Java:
   import static org.apache.spark.sql.functions.*;
   people.select( people.col("age").gt(21) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

lt

public Column lt(Object other)

Less than.

   // Scala: The following selects people younger than 21.
   people.select( people("age") < 21 )

   // Java:
   people.select( people.col("age").lt(21) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

leq

public Column leq(Object other)

Less than or equal to.

   // Scala: The following selects people age 21 or younger than 21.
   people.select( people("age") <= 21 )

   // Java:
   people.select( people.col("age").leq(21) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

geq

public Column geq(Object other)

Greater than or equal to an expression.

   // Scala: The following selects people age 21 or older than 21.
   people.select( people("age") >= 21 )

   // Java:
   people.select( people.col("age").geq(21) )
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

eqNullSafe

public Column eqNullSafe(Object other)

Equality test that is safe for null values.

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

when

public Column when(Column condition,
 Object value)

Evaluates a list of conditions and returns one of multiple possible result expressions. If otherwise is not defined at the end, null is returned for unmatched conditions.

   // Example: encoding gender string column into integer.

   // Scala:
   people.select(when(people("gender") === "male", 0)
     .when(people("gender") === "female", 1)
     .otherwise(2))

   // Java:
   people.select(when(col("gender").equalTo("male"), 0)
     .when(col("gender").equalTo("female"), 1)
     .otherwise(2))
 

Parameters:

condition - (undocumented)

value - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

otherwise

public Column otherwise(Object value)

Evaluates a list of conditions and returns one of multiple possible result expressions. If otherwise is not defined at the end, null is returned for unmatched conditions.

   // Example: encoding gender string column into integer.

   // Scala:
   people.select(when(people("gender") === "male", 0)
     .when(people("gender") === "female", 1)
     .otherwise(2))

   // Java:
   people.select(when(col("gender").equalTo("male"), 0)
     .when(col("gender").equalTo("female"), 1)
     .otherwise(2))
 

Parameters:

value - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

between

public Column between(Object lowerBound,
 Object upperBound)

True if the current column is between the lower bound and upper bound, inclusive.

Parameters:

lowerBound - (undocumented)

upperBound - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

isNaN

public Column isNaN()

True if the current expression is NaN.

Returns:

(undocumented)

Since:

1.5.0

isNull

public Column isNull()

True if the current expression is null.

Returns:

(undocumented)

Since:

1.3.0

isNotNull

public Column isNotNull()

True if the current expression is NOT null.

Returns:

(undocumented)

Since:

1.3.0

or

public Column or(Column other)

Boolean OR.

   // Scala: The following selects people that are in school or employed.
   people.filter( people("inSchool") || people("isEmployed") )

   // Java:
   people.filter( people.col("inSchool").or(people.col("isEmployed")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

and

public Column and(Column other)

Boolean AND.

   // Scala: The following selects people that are in school and employed at the same time.
   people.select( people("inSchool") && people("isEmployed") )

   // Java:
   people.select( people.col("inSchool").and(people.col("isEmployed")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

plus

public Column plus(Object other)

Sum of this expression and another expression.

   // Scala: The following selects the sum of a person's height and weight.
   people.select( people("height") + people("weight") )

   // Java:
   people.select( people.col("height").plus(people.col("weight")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

minus

public Column minus(Object other)

Subtraction. Subtract the other expression from this expression.

   // Scala: The following selects the difference between people's height and their weight.
   people.select( people("height") - people("weight") )

   // Java:
   people.select( people.col("height").minus(people.col("weight")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

multiply

public Column multiply(Object other)

Multiplication of this expression and another expression.

   // Scala: The following multiplies a person's height by their weight.
   people.select( people("height") * people("weight") )

   // Java:
   people.select( people.col("height").multiply(people.col("weight")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

divide

public Column divide(Object other)

Division this expression by another expression.

   // Scala: The following divides a person's height by their weight.
   people.select( people("height") / people("weight") )

   // Java:
   people.select( people.col("height").divide(people.col("weight")) );
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

mod

public Column mod(Object other)

Modulo (a.k.a. remainder) expression.

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

isin

public Column isin(scala.collection.immutable.Seq<Object> list)

A boolean expression that is evaluated to true if the value of this expression is contained by the evaluated values of the arguments.

Note: Since the type of the elements in the list are inferred only during the run time, the elements will be "up-casted" to the most common type for comparison. For eg: 1) In the case of "Int vs String", the "Int" will be up-casted to "String" and the comparison will look like "String vs String". 2) In the case of "Float vs Double", the "Float" will be up-casted to "Double" and the comparison will look like "Double vs Double"

Parameters:

list - (undocumented)

Returns:

(undocumented)

Since:

1.5.0

isInCollection

public Column isInCollection(scala.collection.Iterable<?> values)

A boolean expression that is evaluated to true if the value of this expression is contained by the provided collection.

Note: Since the type of the elements in the collection are inferred only during the run time, the elements will be "up-casted" to the most common type for comparison. For eg: 1) In the case of "Int vs String", the "Int" will be up-casted to "String" and the comparison will look like "String vs String". 2) In the case of "Float vs Double", the "Float" will be up-casted to "Double" and the comparison will look like "Double vs Double"

Parameters:

values - (undocumented)

Returns:

(undocumented)

Since:

2.4.0

isInCollection

public Column isInCollection(Iterable<?> values)

A boolean expression that is evaluated to true if the value of this expression is contained by the provided collection.

Note: Since the type of the elements in the collection are inferred only during the run time, the elements will be "up-casted" to the most common type for comparison. For eg: 1) In the case of "Int vs String", the "Int" will be up-casted to "String" and the comparison will look like "String vs String". 2) In the case of "Float vs Double", the "Float" will be up-casted to "Double" and the comparison will look like "Double vs Double"

Parameters:

values - (undocumented)

Returns:

(undocumented)

Since:

2.4.0

like

public Column like(String literal)

SQL like expression. Returns a boolean column based on a SQL LIKE match.

Parameters:

literal - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

rlike

public Column rlike(String literal)

SQL RLIKE expression (LIKE with Regex). Returns a boolean column based on a regex match.

Parameters:

literal - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

ilike

public Column ilike(String literal)

SQL ILIKE expression (case insensitive LIKE).

Parameters:

literal - (undocumented)

Returns:

(undocumented)

Since:

3.3.0

getItem

public Column getItem(Object key)

An expression that gets an item at position ordinal out of an array, or gets a value by key key in a MapType.

Parameters:

key - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

withField

public Column withField(String fieldName,
 Column col)

An expression that adds/replaces field in StructType by name.

   val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
   df.select($"struct_col".withField("c", lit(3)))
   // result: {"a":1,"b":2,"c":3}

   val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
   df.select($"struct_col".withField("b", lit(3)))
   // result: {"a":1,"b":3}

   val df = sql("SELECT CAST(NULL AS struct<a:int,b:int>) struct_col")
   df.select($"struct_col".withField("c", lit(3)))
   // result: null of type struct<a:int,b:int,c:int>

   val df = sql("SELECT named_struct('a', 1, 'b', 2, 'b', 3) struct_col")
   df.select($"struct_col".withField("b", lit(100)))
   // result: {"a":1,"b":100,"b":100}

   val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2)) struct_col")
   df.select($"struct_col".withField("a.c", lit(3)))
   // result: {"a":{"a":1,"b":2,"c":3}}

   val df = sql("SELECT named_struct('a', named_struct('b', 1), 'a', named_struct('c', 2)) struct_col")
   df.select($"struct_col".withField("a.c", lit(3)))
   // result: org.apache.spark.sql.AnalysisException: Ambiguous reference to fields
 

This method supports adding/replacing nested fields directly e.g.

   val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2)) struct_col")
   df.select($"struct_col".withField("a.c", lit(3)).withField("a.d", lit(4)))
   // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
 

However, if you are going to add/replace multiple nested fields, it is more optimal to extract out the nested struct before adding/replacing multiple fields e.g.

   val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2)) struct_col")
   df.select($"struct_col".withField("a", $"struct_col.a".withField("c", lit(3)).withField("d", lit(4))))
   // result: {"a":{"a":1,"b":2,"c":3,"d":4}}
 

Parameters:

fieldName - (undocumented)

col - (undocumented)

Returns:

(undocumented)

Since:

3.1.0

dropFields

public Column dropFields(scala.collection.immutable.Seq<String> fieldNames)

An expression that drops fields in StructType by name. This is a no-op if schema doesn't contain field name(s).

   val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
   df.select($"struct_col".dropFields("b"))
   // result: {"a":1}

   val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
   df.select($"struct_col".dropFields("c"))
   // result: {"a":1,"b":2}

   val df = sql("SELECT named_struct('a', 1, 'b', 2, 'c', 3) struct_col")
   df.select($"struct_col".dropFields("b", "c"))
   // result: {"a":1}

   val df = sql("SELECT named_struct('a', 1, 'b', 2) struct_col")
   df.select($"struct_col".dropFields("a", "b"))
   // result: org.apache.spark.sql.AnalysisException: [DATATYPE_MISMATCH.CANNOT_DROP_ALL_FIELDS] Cannot resolve "update_fields(struct_col, dropfield(), dropfield())" due to data type mismatch: Cannot drop all fields in struct.;

   val df = sql("SELECT CAST(NULL AS struct<a:int,b:int>) struct_col")
   df.select($"struct_col".dropFields("b"))
   // result: null of type struct<a:int>

   val df = sql("SELECT named_struct('a', 1, 'b', 2, 'b', 3) struct_col")
   df.select($"struct_col".dropFields("b"))
   // result: {"a":1}

   val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2)) struct_col")
   df.select($"struct_col".dropFields("a.b"))
   // result: {"a":{"a":1}}

   val df = sql("SELECT named_struct('a', named_struct('b', 1), 'a', named_struct('c', 2)) struct_col")
   df.select($"struct_col".dropFields("a.c"))
   // result: org.apache.spark.sql.AnalysisException: Ambiguous reference to fields
 

This method supports dropping multiple nested fields directly e.g.

   val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2)) struct_col")
   df.select($"struct_col".dropFields("a.b", "a.c"))
   // result: {"a":{"a":1}}
 

However, if you are going to drop multiple nested fields, it is more optimal to extract out the nested struct before dropping multiple fields from it e.g.

   val df = sql("SELECT named_struct('a', named_struct('a', 1, 'b', 2)) struct_col")
   df.select($"struct_col".withField("a", $"struct_col.a".dropFields("b", "c")))
   // result: {"a":{"a":1}}
 

Parameters:

fieldNames - (undocumented)

Returns:

(undocumented)

Since:

3.1.0

getField

public Column getField(String fieldName)

An expression that gets a field by name in a StructType.

Parameters:

fieldName - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

substr

public Column substr(Column startPos,
 Column len)

An expression that returns a substring.

Parameters:

startPos - expression for the starting position.

len - expression for the length of the substring.

Returns:

(undocumented)

Since:

1.3.0

substr

public Column substr(int startPos,
 int len)

An expression that returns a substring.

Parameters:

startPos - starting position.

len - length of the substring.

Returns:

(undocumented)

Since:

1.3.0

contains

public Column contains(Object other)

Contains the other element. Returns a boolean column based on a string match.

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

startsWith

public Column startsWith(Column other)

String starts with. Returns a boolean column based on a string match.

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

startsWith

public Column startsWith(String literal)

String starts with another string literal. Returns a boolean column based on a string match.

Parameters:

literal - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

endsWith

public Column endsWith(Column other)

String ends with. Returns a boolean column based on a string match.

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

endsWith

public Column endsWith(String literal)

String ends with another string literal. Returns a boolean column based on a string match.

Parameters:

literal - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

alias

public Column alias(String alias)

Gives the column an alias. Same as as.

   // Renames colA to colB in select output.
   df.select($"colA".alias("colB"))
 

Parameters:

alias - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

as

public Column as(String alias)

Gives the column an alias.

   // Renames colA to colB in select output.
   df.select($"colA".as("colB"))
 

If the current column has metadata associated with it, this metadata will be propagated to the new column. If this not desired, use the API as(alias: String, metadata: Metadata) with explicit metadata.

Parameters:

alias - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

as

public Column as(scala.collection.immutable.Seq<String> aliases)

(Scala-specific) Assigns the given aliases to the results of a table generating function.

   // Renames colA to colB in select output.
   df.select(explode($"myMap").as("key" :: "value" :: Nil))
 

Parameters:

aliases - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

as

public Column as(String[] aliases)

Assigns the given aliases to the results of a table generating function.

   // Renames colA to colB in select output.
   df.select(explode($"myMap").as("key" :: "value" :: Nil))
 

Parameters:

aliases - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

as

public Column as(scala.Symbol alias)

Gives the column an alias.

   // Renames colA to colB in select output.
   df.select($"colA".as("colB"))
 

If the current column has metadata associated with it, this metadata will be propagated to the new column. If this not desired, use the API as(alias: String, metadata: Metadata) with explicit metadata.

Parameters:

alias - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

as

public Column as(String alias,
 Metadata metadata)

Gives the column an alias with metadata.

   val metadata: Metadata = ...
   df.select($"colA".as("colB", metadata))
 

Parameters:

alias - (undocumented)

metadata - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

name

public Column name(String alias)

Gives the column a name (alias).

   // Renames colA to colB in select output.
   df.select($"colA".name("colB"))
 

If the current column has metadata associated with it, this metadata will be propagated to the new column. If this not desired, use the API as(alias: String, metadata: Metadata) with explicit metadata.

Parameters:

alias - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

cast

public Column cast(DataType to)

Casts the column to a different data type.

   // Casts colA to IntegerType.
   import org.apache.spark.sql.types.IntegerType
   df.select(df("colA").cast(IntegerType))

   // equivalent to
   df.select(df("colA").cast("int"))
 

Parameters:

to - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

cast

public Column cast(String to)

Casts the column to a different data type, using the canonical string representation of the type. The supported types are: string, boolean, byte, short, int, long, float, double, decimal, date, timestamp.

   // Casts colA to integer.
   df.select(df("colA").cast("int"))
 

Parameters:

to - (undocumented)

Returns:

(undocumented)

Since:

1.3.0

try_cast

public Column try_cast(DataType to)

Casts the column to a different data type and the result is null on failure.

   // Casts colA to IntegerType.
   import org.apache.spark.sql.types.IntegerType
   df.select(df("colA").try_cast(IntegerType))

   // equivalent to
   df.select(df("colA").try_cast("int"))
 

Parameters:

to - (undocumented)

Returns:

(undocumented)

Since:

4.0.0

try_cast

public Column try_cast(String to)

Casts the column to a different data type and the result is null on failure.

   // Casts colA to integer.
   df.select(df("colA").try_cast("int"))
 

Parameters:

to - (undocumented)

Returns:

(undocumented)

Since:

4.0.0

desc

public Column desc()

Returns a sort expression based on the descending order of the column.

   // Scala
   df.sort(df("age").desc)

   // Java
   df.sort(df.col("age").desc());
 

Returns:

(undocumented)

Since:

1.3.0

desc_nulls_first

public Column desc_nulls_first()

Returns a sort expression based on the descending order of the column, and null values appear before non-null values.

   // Scala: sort a DataFrame by age column in descending order and null values appearing first.
   df.sort(df("age").desc_nulls_first)

   // Java
   df.sort(df.col("age").desc_nulls_first());
 

Returns:

(undocumented)

Since:

2.1.0

desc_nulls_last

public Column desc_nulls_last()

Returns a sort expression based on the descending order of the column, and null values appear after non-null values.

   // Scala: sort a DataFrame by age column in descending order and null values appearing last.
   df.sort(df("age").desc_nulls_last)

   // Java
   df.sort(df.col("age").desc_nulls_last());
 

Returns:

(undocumented)

Since:

2.1.0

asc

public Column asc()

Returns a sort expression based on ascending order of the column.

   // Scala: sort a DataFrame by age column in ascending order.
   df.sort(df("age").asc)

   // Java
   df.sort(df.col("age").asc());
 

Returns:

(undocumented)

Since:

1.3.0

asc_nulls_first

public Column asc_nulls_first()

Returns a sort expression based on ascending order of the column, and null values return before non-null values.

   // Scala: sort a DataFrame by age column in ascending order and null values appearing first.
   df.sort(df("age").asc_nulls_first)

   // Java
   df.sort(df.col("age").asc_nulls_first());
 

Returns:

(undocumented)

Since:

2.1.0

asc_nulls_last

public Column asc_nulls_last()

Returns a sort expression based on ascending order of the column, and null values appear after non-null values.

   // Scala: sort a DataFrame by age column in ascending order and null values appearing last.
   df.sort(df("age").asc_nulls_last)

   // Java
   df.sort(df.col("age").asc_nulls_last());
 

Returns:

(undocumented)

Since:

2.1.0

explain

public void explain(boolean extended)

Prints the expression to the console for debugging purposes.

Parameters:

extended - (undocumented)

Since:

1.3.0

bitwiseOR

public Column bitwiseOR(Object other)

Compute bitwise OR of this expression with another expression.

   df.select($"colA".bitwiseOR($"colB"))
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

bitwiseAND

public Column bitwiseAND(Object other)

Compute bitwise AND of this expression with another expression.

   df.select($"colA".bitwiseAND($"colB"))
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

bitwiseXOR

public Column bitwiseXOR(Object other)

Compute bitwise XOR of this expression with another expression.

   df.select($"colA".bitwiseXOR($"colB"))
 

Parameters:

other - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

over

public Column over(WindowSpec window)

Defines a windowing column.

   val w = Window.partitionBy("name").orderBy("id")
   df.select(
     sum("price").over(w.rangeBetween(Window.unboundedPreceding, 2)),
     avg("price").over(w.rowsBetween(Window.currentRow, 4))
   )
 

Parameters:

window - (undocumented)

Returns:

(undocumented)

Since:

1.4.0

over

public Column over()

Defines an empty analytic clause. In this case the analytic function is applied and presented for all rows in the result set.

   df.select(
     sum("price").over(),
     avg("price").over()
   )
 

Returns:

(undocumented)

Since:

2.0.0