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(Add Main Summary MVP) |
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Like the longitudinal dataset, main summary summarizes [https://gecko.readthedocs.io/en/latest/toolkit/components/telemetry/telemetry/data/main-ping.html main pings]. Each row corresponds to a single ping. This table does no sampling and includes all desktop pings. | Like the longitudinal dataset, main summary summarizes [https://gecko.readthedocs.io/en/latest/toolkit/components/telemetry/telemetry/data/main-ping.html main pings]. Each row corresponds to a single ping. This table does no sampling and includes all desktop pings. | ||
===Caveats=== | |||
Querying against main summary on SQL.t.m.o/re:dash can '''impact performance for other users''' and can '''take a while to complete''' (~30m for simple queries). Since main summary includes a row for every ping, there are a large number of records which can consume a lot of resources on the shared cluster. | |||
Instead, we recommend using the Longitudinal dataset where possible if querying from re:dash/sql.t.m.o. The longitudinal dataset samples to 1% of all data and organized the data by client_id. In the odd case where these queries are necessary, limit to a short submission_date_s3 range and ideally make use of the sample_id field. Even better, try using Spark. | |||
==Cross Sectional== | ==Cross Sectional== |
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