GroupedData

Defined in: grouped-data.ts:22

Returned by DataFrame.groupBy, DataFrame.rollup, DataFrame.cube, and related methods. Mirrors RelationalGroupedDataset in the JVM Spark API.

GroupedData is not a DataFrame. It is a transient builder that captures grouping expressions and waits for an aggregation call (agg, count, sum, avg, min, max, pivot) to produce the final DataFrame.

Example

const totals = df.groupBy("department").agg(sum("salary").alias("payroll"));

See

Spark source: RelationalGroupedDataset.scala

Constructors

Constructor

new GroupedData(
   df,
   groupExprs,
   groupType?,
   pivot?): GroupedData;

Defined in: grouped-data.ts:28

Parameters

Parameter	Type	Default value
`df`	`DataFrame`	`undefined`
`groupExprs`	`Expression`[]	`undefined`
`groupType`	`"groupby"` \| `"rollup"` \| `"cube"` \| `"pivot"`	`"groupby"`
`pivot?`	{ `col`: `Expression`; `values`: (`string` \| `number` \| `boolean`)[]; }	`undefined`
`pivot.col?`	`Expression`	`undefined`
`pivot.values?`	(`string` \| `number` \| `boolean`)[]	`undefined`

Returns

GroupedData

Methods

agg()

agg(...exprs): DataFrame;

Defined in: grouped-data.ts:52

Apply one or more aggregate functions.

Parameters

Parameter	Type
…`exprs`	`Column`[]

Returns

DataFrame

Example

df.groupBy(col("dept")).agg(
    functions.sum(col("salary")).alias("total_salary"),
    functions.avg(col("age")).alias("avg_age"),
  )

Each Column passed in should be an aggregate expression (sum, avg, count,
min, max).  The grouping columns are implicitly included in the output.