[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-573778-105":3,"detail-sidebar-cat-1-en-105":80,"doc-detail-573778-en":126},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":73,"head_meta":75,"extra_data":77,"updated_unix":79},105,"en","logql-cheat-sheet-quick-reference-for-log-querying","LogQL Cheat Sheet - Quick reference for log querying","","LogQL Cheat Sheet provides a practical guide to querying FusionReactor logs using LogQL. It explains the structure of basic queries with a log stream selector and an optional filter/search expression. The cheat sheet covers key label matching operators, regex and case-insensitive patterns, supported log filtering operators, and the requirement that all filters apply. It also summarizes counting features, range vector aggregation functions like rate and count_over_time, and aggregation operators such as sum, min, max, avg, and topk/bottomk with by/without grouping.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/template/","Template",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/template/presentations/","Presentations",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/template/logql-cheat-sheet-quick-reference-for-log-querying/573778/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/logql-cheat-sheet-quick-reference-for-log-querying/573778.png","ImageObject",442,249,{"name":42,"@type":43},"Noah","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-15","2026-10-14",true,{"@type":52,"interactionType":53,"userInteractionCount":30},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"What are the two parts of a basic LogQL query?","Question",{"text":62,"@type":63},"A basic LogQL query includes a log stream selector and, optionally, a filter/search expression.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"Which label matching operators does LogQL support?",{"text":67,"@type":63},"It supports regex match (=~), regex non-match (!~), exact equal (=), and not equal (!=).",{"name":69,"@type":60,"acceptedAnswer":70},"How does LogQL count logs over time?",{"text":71,"@type":63},"Use range vector aggregation functions such as count_over_time to count entries per log stream within a time range, or rate to compute per-second entry rates.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},573778,1792032708,{"code":4,"msg":81,"data":82},"success",[83,87,92,97,102,107,112,117,122],{"id":84,"doc_module":22,"doc_module_name":25,"category_name":29,"show_sort_weight":85,"slug":86},11,90,"presentations",{"id":88,"doc_module":22,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},12,"Resumes",80,"resumes",{"id":93,"doc_module":22,"doc_module_name":25,"category_name":94,"show_sort_weight":95,"slug":96},14,"Invoices",70,"invoices",{"id":98,"doc_module":22,"doc_module_name":25,"category_name":99,"show_sort_weight":100,"slug":101},15,"Posters",60,"posters",{"id":103,"doc_module":22,"doc_module_name":25,"category_name":104,"show_sort_weight":105,"slug":106},16,"Social Media",50,"social-media",{"id":108,"doc_module":22,"doc_module_name":25,"category_name":109,"show_sort_weight":110,"slug":111},17,"Forms",40,"forms",{"id":113,"doc_module":22,"doc_module_name":25,"category_name":114,"show_sort_weight":115,"slug":116},18,"Letters",30,"letters",{"id":118,"doc_module":22,"doc_module_name":25,"category_name":119,"show_sort_weight":120,"slug":121},21,"Paper Templates",5,"papers-templates",{"id":123,"doc_module":22,"doc_module_name":25,"category_name":124,"show_sort_weight":4,"slug":125},158,"General","general-158",{"code":4,"msg":81,"data":127},{"doc_id":78,"user_id":128,"nickname":42,"user_avatar":129,"doc_module":22,"category_id":84,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":30,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":26,"language":135,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":12,"update_tm":139,"read_time":22},8796095462418,"https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780","[Fusion-Reactor.com](Fusion-Reactor.com)  \nLogQL Cheat Sheet  \nThis cheat sheet highlight different pattern for querying FusionReactor LogQL.  \nIntroducing LogQL log query Language  \nFusionReactor queries log with its unique log query language called LogQL, often distributed as grep besides labels for filtering. There are two parts of a basic LogQL: the filter expression and the log stream selector.  \nAll LogQL queries contain a log streaming selector. The log stream selector does most of the work. It filters the logsand reduces the log volume. This stream collector impacts the performance of the query's execution, depending on the number of labels used to filter down the log streams.  \nLog Stream Selector  \nThe primary function of the log stream selector is to select and organize which log selector will query streams. At least one or more key-value pairs are found in the stream selector, which makes up the log label's value. This key-value pairs are closely enclosed in a pair of curly braces:  \n{app=\"mysql\", name=\"mysql-backup\"}  \nIn the example above, we can see that the log streams contain a label of the app whose value is Mysql and a name whose value is in the query results. The = represents the label matching operator. This does not limit the following label matching operators when querying logs:  \n● = ~ : regex matches.  \n● ! ~ : regex does not match.  \n● =: exactly equal.  \n● !=: not equal.  \nAnother example:  \n{ name= ~ \"mysql.+\"}{name! ~ \"mysql.+\"}  \nFusionReactor and Prometheus apply the same rules when selecting labels.  \nFilter expressions  \nAfter filtering the logs through the log stream selector in FusionReactor, the resulting set of logs can be further filtered with a search expression The search expression can be just text or regex:  \n● {job=\"mysql\"} |= \"error\"  \n● { name=\"kafka\"} | ~ \"tsdb-ops.* io:2003\"  \n● {instance= ~ \"kafka-[23]\", name=\"kafka\"} != kafka.server:type= ReplicaManager  \nThe following filter operators are supported when querying logs:  \n● |=: Log line contains a string.  \n● !=: Log line does not contain a string.  \n● | ~ : Log line matches the regular expression.  \n● ! ~ : Log line does not match the regular expression.  \nNote. that all log lines should match every filter expression, regardless of how to filter operators are channeled for search expression:  \n{job=\"mysql\"} |= \"error\" != \"timeout\"  \nWhen using | ~ and ! ~, Go RE2 syntax regex may be used. By default, the matching is case-sensitive and can be switched to case-insensitive, prefixing the regex with (?i) .  \n[Fusion-Reactor.com](Fusion-Reactor.com)  \nCounting Logs  \nAnother exciting feature of LogQL is t hat it can envelop a query and allow the log stream selector to count entries per stream.  \nRange Vector Aggregation  \nLogQL range vector is unique from other log language queries because the selected range of samples usually includes a value of 1 for each entry. Hence, the aggregate can envelop a selected range into an instance vector. The range vector supported functions are:  \n● rate: calculate the number of entries per second  \n● count_over_time: counts the entries for each log stream within the given range.  \n● count_over_time({job=\" MySQL\"} [5m]) For instance, the range vector counts all the log lines among the fi rst 5 minutes for the MySQL query. This example showcases the per-second rate of all non timeout errors  \nrate:  \n( ( {job=\"mysql\"} |= \"error\" != \"timeout) [10s] ) )  \nAggregation operators  \nLogQL aggregation operators act similarly to PromQL, which supports a subset that can aggregate the elements of a single vector. This action results in anew vector of fewer elements with aggregated values.  \n● sum: Calculate the sum over labels  \n● min: Select minimum over labels  \n● max: Select maximum over labels  \n● avg: Calculate the average over labels  \n● stddev: Calculate the population standard deviation over labels  \n● stdvar: Calculate the population standard variance over labels  \n● count: Count the number of elements in the vect","cbCaiqW56bQKjv3i","https://ap.wps.com/l/cbCaiqW56bQKjv3i","pdf",119043,"English","# LogQL Query Basics\n## Log Stream Selector and Label Matching\n## Filter Expressions and Operators\n## Counting Logs and Range Vector Aggregation\n## Aggregation Operators and Grouping","[{\"question\":\"What are the two parts of a basic LogQL query?\",\"answer\":\"A basic LogQL query includes a log stream selector and, optionally, a filter/search expression.\"},{\"question\":\"Which label matching operators does LogQL support?\",\"answer\":\"It supports regex match (=~), regex non-match (!~), exact equal (=), and not equal (!=).\"},{\"question\":\"How does LogQL count logs over time?\",\"answer\":\"Use range vector aggregation functions such as count_over_time to count entries per log stream within a time range, or rate to compute per-second entry rates.\"}]","LogQL Cheat Sheet - Quick reference for log querying | PDF",1791945916]