Data Processing Language (DPL)

DPL automatically connects to the Teragrep Archive without any extra configuration.

With DPL you can make data searches by using different kind of criteria. The simplest dpl command contains only the dataset’s name.

To narrow down the results, you can add date range by using either earliest=, latest= or both.

You can also add keywords to narrow down the results. The following example uses keyword 997913837433 which will fetch all records that contain it.

You can use multiple criteria at the same time. The following example searches all records that:

To see more available DPL commands, read transforms, aggregations and evaluations.

You can create pivot tables with dataset’s name, chart and an aggregation. chart and the aggregation needs to be separated from the dataset’s name with |. The following example will use count() aggregation.

As in picture, the example will create a single column table. You can aggregate more than one column, just use comma between aggregations.

Use by to group your aggregated values.

You can use data search criteria with aggregations. The following example aggregates all data:

See the comprehensive list of DPL aggregations here.

DPL produces the data into a Spark Query named after the paragraph’s unique identifier. (You can see each paragraph’s identifier from the Paragraph Settings menu.) This output can then be processed with other interpreters that belong to the same interpreter group.