Analytics SAQL Developer Guide
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SAQL Statements
A query is made up of statements. Each SAQL statement has an input stream, an operation,
and an output stream.
-
arimax
Uses existing data to predict future data points. The arimax statement must follow a projection statement in your query. Perform any filtering pre-projection or after the arimax statement. -
cogroup
Use cogroup to combine data from two or more data streams into a single data stream. The data streams must have at least one common field. -
fill
Use fill() to fill in any gaps in date fields. You most often use fill() before using the timeseries statement. By specifying the date fields to check, fill() creates a row that contains the missing month, day, week, quarter, or year and includes a null value. To include values outside the bounds of your data’s date range, specify a start date and end date to override existing limits. The function returns the missing date rows with null values. -
filter
Selects rows from a dataset based on a filter predicate. -
foreach
Applies a set of expressions to every row in a dataset. This action is often referred to as projection. -
group-by
Organizes the rows returned from a query into groups. Within each group, you can apply an aggregate function, such as count() or sum() to get the number of items or sum, respectively. -
group-by rollup
rollup is a subclause of group-by that creates and displays aggregations of grouped data. The output of rollup is based on column order in your query. -
join semi and anti
Use the join statement with the join_type to create semi-join or anti-join results. -
limit
Limits the number of results that are returned. If you don’t set a limit, queries return a maximum of 10,000 rows. -
load
Loads a dataset. All SAQL queries start with a load statement. -
offset
Use offset to page through the results of your query. -
order
Sorts in ascending or descending order on one or more fields. -
sample
Returns a random sample from a large dataset, where each data point has an equal probability of being selected. This keyword uses the Bernoulli distribution. -
timeseries
Uses existing data to predict future data points. The timeseries statement must follow a projection statement in your query. Perform any filtering pre-projection or after the timeseries statement. -
union
Combines multiple result sets into one result set. The result sets must have the same field names and structure. You can use a different dataset to create each result set, or you can use the same dataset.