foreach

Applies a set of expressions to every row in a dataset. This action is often referred to as projection.

The output column names are specified with the as keyword. The output data is ungrouped.

When used with ungrouped data, the foreach statement maps the input rows to output rows. The number of rows remains the same.

a2 = foreach a1 generate carrier as carrier, miles as miles;

When used with grouped data, the foreach statement behaves differently than it does with ungrouped data.

Fields can be directly accessed only when the value is the same for all group members. For example, the fields that were used as the grouping keys have the same value for all group members. Otherwise, use aggregate functions to access the members of a group. The type of the column determines which aggregate functions you can use. For example, if the column type is numeric, you can use the sum() function.

z = foreach y generate day as day, unique(origin) as uorg, count() as n;

To create logic in a foreach statement that chooses between conditional statements, use a case expression.

Each field name in a projection must be unique and not have the name ‘none’. Invalid field names throw an error.

For example, the last line in this query is invalid because the same name is used for multiple projected fields:

The following query is also invalid because the projected field name can’t be ‘none’.

For examples of projections, see Calculate Grand Totals and Subtotals with the rollup Modifier and grouping() Function.

See Also

• Statements