Use queries to identify the exact log records you want Cortex Data Lake to retrieve.
Queries are Boolean expressions that identify the log records Cortex Data Lake will retrieve for the specified log record type. You use them as an addition to the log record type and time range information that you are always required to provide. Use queries to narrow the retrieval set to the exact records you want.
Specify queries using match statements. These statements can be either an equality or pattern matching expression. You can optionally combine these statements using the Boolean operators:
<match_statement> [<boolean> <match_statement>] ...
source_user LIKE 'paloalto%' AND action.value = 'deny'
A query can be at most 4096 characters long. The actual field name that you use for your filters are not identical to the names shown in the column header. Also, the data displayed in the log table might not always be the identical value you want to use in your queries. For example, the
BYTESfield shows values rounded to the nearest byte or kilobyte. To obtain the exact bytes_total value, use the add-to-search feature provided by the query builder.
The filter evaluates queries according to the standard order of precedence for logical operators. However, you can change the order of operations by grouping terms in parentheses.
It is an error to create a query with identical start and end times.
Equality operators are described below.
Pattern matching is supported only for fields that contain strings or IP addresses.
For strings and IP addresses,
%may be provided as a wild card character at any location in the value. A pattern matching expression that does not provide a wild card returns the identical log lines as an equality comparison.
You must use single quotes with your string values: '<
value>'. Double quotes are illegal: "<
When building a query, you can choose from a set of operators. The following table describes when to use each operator and lists its compatible values.
When to Use it
Find logs that contain an exact value.
bytes_total = 270
action.value = 'allow'
src_ip.value = “220.127.116.11/32”
src_ip.value = “18.104.22.168/24”
time_generated = '2022-03-29 12:57:14'
!= or <>
Find logs that do not contain anexact value.
bytes_total != 270
bytes_total <> 270
action.value != 'allow'
action.value <> 'allow'
src_ip.value != “22.214.171.124/32”
src_ip.value <> “126.96.36.199/24”
time_generated != '2022-03-29 12:57:14'
time_generated <> '2022-03-29 12:57:14'
Find logs with data less than a value.
bytes_total < 270
time_generated < '2022-03-29 12:57:14'
Find logs with data less than or equal to a value.
bytes_total <= 270
time_generated <= '2022-03-29 12:57:14'
Find logs with data greater than a value.
bytes_total < 270
time_generated > '2022-03-29 12:57:14'
Find logs with data greater than or equal to a value.
bytes_total <= 270
time_generated >= '2022-03-29 12:57:14'
Find logs with data that matches a string pattern.
LIKEis not supported for fields such as
protothat have limited possible values.
source_user_info.name LIKE “usern_me”
You can use either
%as wildcard characters.
Find logs that satisfy multiple search terms at once.
bytes_total = 270 AND
source_user_info.name LIKE “usern_me” AND src_ip.value != “188.8.131.52/24”
Find logs that satisfy at least one of multiple search terms.
bytes_total = 270 OR source_user_info.name LIKE “usern_me” OR src_ip.value != “184.108.40.206/24”
Specify the priority in which search terms are evaluated.
bytes_total = 270 AND (source_user_info.name LIKE “usern_me” OR src_ip.value != “220.127.116.11/24”)
About Field Names
The field names that you use in your queries are sometimes, but not always, identical to the names shown in the log record column headers. The field name that you must use is the log record field name as it is stored in Cortex Data Lake. There are two ways to obtain this field name:
- Click into the user interface query field to see a drop-down list of available field names for the selected log type. On the right-hand side of this drop-down list is the corresponding column name.
- The Explore Schema Reference guide provides a mapping of the log column name, as shown in the user interface, to the corresponding log record field name.
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