Column (Spark 3.1.3 JavaDoc)

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

Note:

The internal Catalyst expression can be accessed via expr, but this method is for debugging purposes only and can change in any future Spark releases.

Constructor Summary

Constructors
Constructor and Description

Column(org.apache.spark.sql.catalyst.expressions.Expression expr)

Column(String name)

Constructors
Constructor and Description
`Column(org.apache.spark.sql.catalyst.expressions.Expression expr)`
`Column(String name)`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and 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.
`<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.Seq<String> aliases)` (Scala-specific) Assigns the given aliases to the results of a table generating function.
`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.
`Column`	`as(scala.Symbol alias)` Gives the column an alias.
`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`	`asc()` Returns a sort expression based on ascending order of the column.
`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(DataType to)` Casts the column to a different data type.
`Column`	`cast(String to)` Casts the column to a different data type, using the canonical string representation of the type.
`Column`	`contains(Object other)` Contains the other element.
`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`	`desc()` Returns a sort expression based on the descending order of the column.
`Column`	`divide(Object other)` Division this expression by another expression.
`Column`	`dropFields(scala.collection.Seq<String> fieldNames)` An expression that drops fields in `StructType` by name.
`Column`	`endsWith(Column other)` String ends with.
`Column`	`endsWith(String literal)` String ends with another string literal.
`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.
`org.apache.spark.sql.catalyst.expressions.Expression`	`expr()`
`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`	`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.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(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`	`isInCollection(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).
`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(Column other)` String starts with.
`Column`	`startsWith(String literal)` String starts with another string literal.
`Column`	`substr(Column startPos, Column len)` An expression that returns a substring.
`Column`	`substr(int startPos, int len)` An expression that returns a substring.
`String`	`toString()`
`static scala.Option<org.apache.spark.sql.catalyst.expressions.Expression>`	`unapply(Column col)`
`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 Object
getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.internal.Logging
$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize

Constructor Detail

Column

public Column(org.apache.spark.sql.catalyst.expressions.Expression expr)

Column
```
public Column(String name)
```

Method Detail

unapply

public static scala.Option<org.apache.spark.sql.catalyst.expressions.Expression> unapply(Column col)

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

expr

public org.apache.spark.sql.catalyst.expressions.Expression expr()

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.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

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.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: cannot resolve 'update_fields(update_fields(`struct_col`))' 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.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

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

Class Column

Constructor Summary

Method Summary

Methods inherited from class Object

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

Constructor Detail

Column

Column

Method Detail

unapply

isin

expr

toString

equals

hashCode

as

apply

equalTo

notEqual

gt

lt

leq

geq

eqNullSafe

when

otherwise

between

isNaN

isNull

isNotNull

or

and

plus

minus

multiply

divide

mod

isin

isInCollection

isInCollection

like

rlike

getItem

withField

dropFields

getField

substr

substr

contains

startsWith

startsWith

endsWith

endsWith

alias

as

as

as

as

as

name

cast

cast

desc

desc_nulls_first

desc_nulls_last

asc

asc_nulls_first

asc_nulls_last

explain

bitwiseOR

bitwiseAND

bitwiseXOR

over

over