| statssum(num)asnums # stats 命令后面通常跟聚合函数,如 count, sum, avg 等 5. eval - 用于计算表达式并将结果赋值给新字段 |evalversion = split(version,",") |evalversion = mvindex(version,0) # 拓展:加减乘除运算 |evalsum= field1 + field2# 加 |evaldifference = field1 - field2# 减...
ERROR clientip=/8 | stats sum (bytes) by clientip | search sum 1048576 计计算命令前使⽤筛筛选选命令 在命令执⾏计算 (如 eval)之前使⽤筛选命令 (如 where)。 例如,此搜索的 eval 命令后有⼀个 where 命令。运⾏ where 命令之前,搜索不需要 eval 命令结果。 field1=value | eval KB=...
|stats sum(eval(if(b_failed="false",1,0))) as success_count, sum(eval(if(b_failed="false",0,1))) as failed_count 1 Karma Reply isoutamo SplunkTrust 06-02-2021 07:15 AM Hi check stats + eval from this page https://docs.splunk.com/Documentation/Splunk/8.2.0/SearchRe...
| stats sum(Users) as UserLogins, sum(Documents) as DocumentUploads, sum(LoansSD) as CreatedSD, sum(LoansBD) as CreatedBD, sum(LoansLOD) as CreatedLOD by source| eval CreatedTotal = CreatedSD + CreatedBD + CreatedLOD| rename source as SERVICE 1 Karma Reply richgalloway SplunkTr...
... | streamstats sum(bytes) as bytes _ total \| timechartrow_cumsum...\| serialize cs=row_cumsum(bytes) anomalydetection查找指定字段中的异常。 SPL 示例series_decompose_anomalies()KQL 示例 where使用eval表达式筛选搜索结果。 用于比较两个不同的字段。whereT | where fruit=="apple" ...
index="_internal" source="*metrics.log" group="per_sourcetype_thruput" | eval MB=kb/1024 | chart sum(MB) avg(eps) over series If we are having trouble with data input and we want a way to troubleshoot it, particularly if our whitelist/blacklist rules are not working the way we exp...
... | streamstats sum(bytes) as bytes _ total \| timechart row_cumsum ...\| serialize cs=row_cumsum(bytes) anomalydetection 在指定的欄位中尋找異常。SPL 範例 series_decompose_anomalies() KQL 範例 where 使用eval 運算式篩選搜尋結果。 用來比較兩個不同的欄位。 where T | where fruit=="...
| addinfo | eval bucket_span=info_max_time - _time | eval bucket_span=if(bucket_span > 3600, 3600, bucket_span) Lastly, calculate the rate with the following functionrate = delta_count/time_range. | eval rate_hits=sum_hits/bucket_span | fields - sum_hits, bucket_span, info_max_...
count where index=* AND TERM({{ENTITY}}) by index, sourcetype | convert ctime(first_seen) ctime(last_seen) | stats values(index), values(sourcetype), min(first_seen),max(last_seen),sum(count) | rename values(index) as indexes, values(sourcetype) as sourcetypes | eval entity="{{ENTIT...
| stats count AS event_count sum(bytes_in) AS bytes_in sum(bytes_out) AS bytes_out sum(bytes) as bytes_total by src_ip dest_ip | eval mb_in=round((bytes_in/1024/1024),2) | eval mb_out=round((bytes_out/1024/1024),2) | eval mb_total=round((bytes_total/1024/1024),2) ...