Searches automatically pause after 100,000 results are found. Using an efficient query can help you avoid this limitation.
Make the search as selective as possible
The more specific the query, the more efficiently it will run, as unnecessary messages are quickly thrown out of the mix. For example, the following two queries will generate the same result:
* | parse regex "uid=(?<userId>\d+)"
"uid=" | parse regex "uid=(?<userId>\d+)"
The second query will return the results more efficiently because the first query includes "
*", which prompts Sumo Logic to comb through all messages for the given time range.
Use Field Extraction Rules
If your admin has created Field Extraction Rules, learn how to use them. Field Extraction Rules parse out fields from your organization's log files, meaning that you won't need to parse out fields in your query.
Include the most selective filters first
It's best to filter data as early as possible in the query, using the most selective filters first.
For example, look at the following queries:
* | parse "queryTime=* " as queryTime | parse "uid=* " as uid | where queryTime > 10000
* | parse "queryTime=* " as queryTime | where queryTime > 10000 | parse "uid=* " as
Because most log lines have a uid, but only a small fraction have queryTime > 10000, the second query is more efficient.