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Use this Snap to add aggregate functions such as COUNT, SUM, MIN, and MAX along with the GROUP BY clause in the incoming SQL query. GROUP BY clauses are used to group table records based on columns that contain classifying data and are optional in this Snap. This Snap also allows you to preview the result of the output query. You can validate the modified query using this preview functionality. The supported aggregate functions vary based on the account configuration. See the description of the Aggregate Function field in the Snap Settings section for details.

Prerequisites

None.

Limitations

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Parameter Name

Data Type

Description

Default Value

Example

Label

String

Insert excerpt

	File Writer
	File Writer
nopanel	true

ELT Aggregate

Aggregate Revenue

Get preview data

Checkbox

Multiexcerpt include macro

name	getpreviewdata
page	ELT Intersect

Not selected

Selected

General Aggregate Functions List

This field set enables you to specify the columns for which to add the aggregate functions. Each aggregate function must be specified as a new row. Click to add a row.

This field set contains the following fields:

Function
Argument
Eliminate duplicates
Alias Name

Function*

String/Expression/Suggestion

Required. Select the aggregate function to use. Click to retrieve the list of the supported aggregate functions. The list displays the functions supported by the database that you select in the Account settings. An error is displayed if an account is not configured. See the Troubleshooting section for details.

Alternatively, you can also enter the name of the aggregate function to use; you must, however, ensure that it is spelled correctly. Otherwise, the Snap displays an error.

You can use the following aggregate functions:

AVG
COUNT
COUNT_IF
MAX
MIN
SUM
SKEW
MODE
KURTOSIS

Additionally, the following aggregate functions are available based on the database type:

Snowflake	Redshift	Azure Synapse
ANY_VALUE BITAND_AGG BITOR_AGG BITXOR_AGG BOOLAND_AGG BOOLOR_AGG BOOLXOR_AGG MEDIAN STDDEV STDDEV_POP STDDEV_SAMP VAR_POP VAR_SAMP	APPROXIMATE.COUNT BIT_AND BIT_OR BOOL_AND BOOL_OR MEDIAN STDDEV_POP STDDEV_SAMP VAR_POP VAR_SAMP	APPROX_COUNT_DISTINCT COUNT_BIG GROUPING STDEV STDEVP VAR VARP
Databricks Lakehouse Platform		BigQuery
ANY BIT_OR BIT_XOR BOOL_AND BOOL_OR COLLECT_LIST COLLECT_SET EVERY FIRST_VALUE_RESPECT_NULLS FIRST_VALUE_IGNORE_NULLS LAST_VALUE_RESPECT_NULLS LAST_VALUE_IGNORE_NULLS SOME SKEWNESS STDDEV STDDEV_POP STDDEV_SAMP VAR_POP VAR_SAMP		ANY_VALUE BIT_AND BIT_OR BIT_XOR LOGICAL_AND LOGICAL_OR

See Snowflake Aggregate Functions, Redshift SQL Functions Reference, Aggregate Functions (Transact-SQL), Databricks Built-in Functions Reference, or BigQuery Aggregate Functions in Standard SQL for more information on the respective aggregate function.

N/A

AVG

Argument*

String/Expression

Required. Enter the field name or expression on which you want to apply the general aggregate function.

N/A

REVENUE

Eliminate duplicates

Check box

Select to apply DISTINCT to the column specified in the Field field. This means that the aggregate function is applied only to the unique values in the column.

Note

title	Behavior with COUNT_IF aggregate function

Selecting this checkbox while using COUNT_IF aggregate function does not eliminate duplicate records in case of Snowflake and BigQuery databases, as there is no native support. However, it eliminates the duplicates from the list of records when used with a Redshift, Azure Synapse, or Databricks Lakehouse Platform (DLP) instance.

Not selected

Selected

Alias Name*

String

Required. Specify the column in which to display the result of the aggregate function. You can also reference this name in downstream Snaps to process the data further.

N/A

TOTAL_REVENUE

Linear Regression Aggregate Functions List

This field set enables you to specify the columns for which to apply the linear regression aggregate functions. Each function must be specified as a new row. Click to add a row.

This field set contains the following fields:

Function
Argument 1
Argument 2
Alias Name

Function*

String/Expression/Suggestion

Required. Select the aggregate function to use. Click to retrieve the list of the supported linear regression aggregate functions. The list displays the functions supported by the database. An error is displayed if an account is not configured. See the Troubleshooting section for details.

Alternatively, you can also enter the name of an aggregate function; you must, however, ensure that it is spelled correctly. Otherwise, the Snap displays an error.

You can use the following aggregate functions:

CORR
COVAR_POP
COVAR_SAMP
REGR_AVGX
REGR_AVGY
REGR_COUNT
REGR_INTERCEPT
REGR_R2
REGR_SLOPE
REGR_SXX
REGR_SXY
REGR_SYY
MINHASH (for Snowflake only)
OBJECT_AGG (for Snowflake only)

See Snowflake Aggregate Functions, Databricks Built-in Functions Reference, or BigQuery Aggregate Functions in Standard SQL for more information on the respective aggregate function.

Info

title	Though not supported natively

BigQuery does not natively support the above list of Linear Regression Aggregate Functions. However, SnapLogic provides you with the ability to use these functions with BigQuery through a series of internal query rewrites.

N/A

CORR

Argument 1*

String/Expression

Required. Enter the first field name or expression on which you want to apply the Aggregate function.

N/A

REVENUE_LOC1

Argument 2*

String/Expression

Required. Enter the second field name or expression on which you want to apply the Aggregate function.

N/A

REVENUE_LOC2

Alias Name*

String

Required. Specify the column in which to display the result of the aggregate function. You can also reference this name in downstream Snaps to process the data further.

N/A

LINREGAGG_REVENUE

Aggregate Concatenation Functions List (Not valid for Databricks Lakehouse Platform)

This field set enables you to specify the list of aggregate concatenation functions to be used for aggregation. The list displays the functions supported by the database that you select in the Account settings. Each function must be specified as a new row. Click to add a row.

This field set contains the following fields:

Aggregate Concatenation Function
Field Name
Alias Name
Delimiter

Function*

String/Expression/Suggestion

Required. Select the aggregate concatenation function to use. Click to retrieve the list of the supported functions. The list displays the functions supported by the database that you select in the Account settings. An error is displayed if an account is not configured. See the Troubleshooting section for details.

Alternatively, you can also enter the name of the aggregate concatenation function to use; you must, however, ensure that it is spelled correctly. Otherwise, the Snap displays an error.

You can use the following aggregate functions:

Snowflake	Redshift	Azure Synapse
LISTAGG LISTAGG_DISTINCT ARRAY_AGG ARRAY_AGG_DISTINCT	LISTAGG DISTINCT_LISTAGG	STRING_AGG
BigQuery
ARRAY_AGG ARRAY_AGG_DISTINCT ARRAY_CONCAT_AGG STRING_AGG STRING_AGG_DISTINCT

See Snowflake Aggregate Functions, Redshift SQL Functions Reference, Aggregate Functions (Transact-SQL), or BigQuery Aggregate Functions in Standard SQL for more information on the respective aggregate function.

N/A

LISTAGG

Argument*

String/Expression

Required. Enter the field name or expression on which you want to apply the Aggregate Concatenation function.

N/A

NEW_LOCATIONS

Alias Name*

String

Required. Specify the column in which to display the result of the concatenation function. You can also reference this name in downstream Snaps to process the data further.

N/A

UNIQUE_LOCS_LIST

Delimiter

String/Expression

Specify the delimiting character (string constant) to be used to separate the concatenated values.

, (comma)

; (semi-colon)

Percentile Distribution Functions List (Not valid for Azure Synapse, Databricks Lakehouse Platform, BigQuery)

This field set enables you to specify the list of percentile distribution functions to be used for aggregation. The list displays the functions supported by the database that you select in the Account settings. Each function must be specified as a new row. Click to add a row.

This field set contains the following fields:

Function
Percentile
Alias Name

Function*

String/Expression/Suggestion

Required. Select the percentile distribution function to use. Click to retrieve the list of the supported functions. The list displays the functions supported by the database that you select in the Account settings. An error is displayed if an account is not configured. See the Troubleshooting section for details.

Alternatively, you can also enter the name of the percentile distribution function to use; you must, however, ensure that it is spelled correctly. Otherwise, the Snap displays an error.

You can use the following aggregate functions:

Snowflake	Redshift
PERCENTILE_DISC PERCENTILE_CONT	APPROXIMATE_PERCENTILE_DISC PERCENTILE_CONT

See Snowflake Aggregate Functions or Redshift SQL Functions Reference for more information on the respective aggregate function.

N/A

PERCENTILE_DISC

Percentile*

String/Expression

Required. Specify the percentile value to be considered for applying the percentile distribution function.

N/A

0.8 (80th percentile)

Alias Name*

String

Required. Specify the column in which to display the result of the percentile distribution function. You can also reference this name in downstream Snaps to process the data further.

N/A

REVENUE_CPERCENTILE

Group By All The Input Columns

Checkbox

Select this checkbox to group the output data by all columns in the input table. This disables the Group By Arguments List fieldset.

Not Selected

Selected

GROUP BY Arguments List

This fieldset enables you to specify the columns for which to use the GROUP BY clause. Each column must be specified in a new row. Click to add a row.

This fieldset contains the following field:

Argument

Argument

String/Expression

Specify the column in which to add the GROUP BY clause.

N/A

GRADE

GENDER

GROUP BY CUBE

Checkbox

Select this checkbox to group the output data using the GROUP BY CUBE clause. This activates the GROUP BY CUBE Arguments List fieldset.

Not Selected

Selected

GROUP BY CUBE Arguments List

This fieldset enables you to specify the arguments for the GROUP BY CUBE clause. In addition to the GROUP BY ROLLUP, GROUP BY CUBE adds all the “cross-tabulations” rows and is equivalent to a series of grouping sets. Each argument must be specified in a new row. Click to add a row.

This fieldset contains the following field:

Argument

Argument*

String/Expression

Specify the column in which to add the GROUP BY CUBE clause.

N/A

CUST_ID

ORDERS

GROUP BY ROLLUP

Checkbox

Select this checkbox to group the output data using the GROUP BY ROLLUP clause. This activates the GROUP BY ROLLUP Arguments List fieldset.

Not Selected

Selected

GROUP BY ROLLUP Arguments List

This fieldset enables you to specify the arguments for the GROUP BY ROLLUP clause that produces sub-total rows (in addition to the grouped rows). Each argument must be specified in a new row. Click to add a row.

This fieldset contains the following field:

Argument

Argument*

String/Expression

Specify the column in which to add the GROUP BY ROLLUP clause.

N/A

CATEGORY

REGION

GROUP BY GROUPING SETS

Checkbox

Select this checkbox to group the output data using the GROUP BY GROUPING SETS clause. This activates the GROUP BY GROUPING SETS Arguments List fieldset.

Not Selected

Selected

GROUP BY GROUPING SETS Arguments List

This fieldset enables you to specify the arguments for the GROUP BY GROUPING SETS clause that that allows computing multiple GROUP BY clauses in a single statement. The group set is a set of dimension columns. Each argument must be specified in a new row. Click to add a row.

This fieldset contains the following field:

Argument

Argument*

String/Expression

Specify the column in which to add the GROUP BY GROUPING SETS clause.

N/A

CATEGORY

REGION

HAVING Predicate List

This fieldset enables you to specify the arguments for the HAVING predicates (conditions) over the result of applying a GROUP BY clause. Each predicate must be specified in a new row. Click to add a row.

This fieldset contains the following field:

Predicate
Boolean Operator

Predicate

String/Expression

Specify the predicate (condition) to filter the results of a GROUP BY (CUBE/ROLLUP/GROUPING SETS) operation.

N/A

ORD_COUNT(*) >100

Boolean Operator

Drop-down list

Select one boolean operator to apply another HAVING predicate in combination with the predicate selected.

N/A

AND

ORDER-BY Fields (Aggregate Concatenation Functions Only)

This field set enables you to specify the columns by which to sort the output data set. Each column must be specified in a new row. Click + to add a row.

This field set contains the following fields:

ORDER BY Field
Sort Order
Null Value Sort Preference

ORDER BY Field

String/Expression

Specify the column by which to sort the output data set.

N/A

GRADE

GENDER

Sort Order

Drop-down list

Choose one of the possible sort orders - ASC (ascending) or DESC (descending) for the output data set.

ASC

DESC

Null Value Sort Preference

Drop-down list

Choose where in the sort order do the null values, if any, in the ORDER BY Field be placed - NULLS FIRST (at the beginning) or NULLS LAST (at the end)

NULLS FIRST

NULLS LAST

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Versions Compared

Old Version 37

New Version 38

Key

Prerequisites

Limitations