JQL, or Jira Query Language, is one of the most powerful features in Jira because it allows users to search for issues using precise conditions. When teams rely on large backlogs or when projects accumulate hundreds of work items they need a consistent way to filter and locate information. JQL provides that capability by letting you describe exactly what you are looking for using fields, operators and values written in natural language. Once you understand how JQL handles concepts like null, empty and not empty you can write queries that return exactly the items you want and nothing you do not.
Many Jira fields accept multiple values or allow the field to remain blank. Labels are a common example. Versions, components and custom fields behave in similar ways. A blank field in Jira can appear in search results in several different forms. Sometimes it can be literally empty. Sometimes it can be stored as a null value, meaning the field has no data at all. From the user’s perspective empty and null feel identical. The field shows nothing. But when JQL evaluates the field it distinguishes these cases because they represent different states in the underlying data. Jira therefore provides multiple ways to search for blank values so that your query can match what you actually want to find.
When you write a JQL search such as labels is empty or labels equals empty you are telling Jira to return issues where the field contains no values. This means the user never added any labels to the issue. From Jira’s perspective this is one of the simplest evaluations to perform. It checks the field and confirms there are no stored entries. Because empty fields are so common Jira supports several interchangeable forms of that idea including labels is empty, labels equals empty, labels in empty and even labels in null. All of these variations work because they all point to the same outcome, which is that the field contains nothing.
JQL also understands the concept of null which is slightly different. When a field is null the system is storing the absence of a value rather than an actual empty list. For most users these two ideas look identical but JQL allows you to query for them using expressions like labels equals null or labels in null. The reason this matters is that Jira’s indexing system can treat null values differently from empty values depending on the field. To make searching easier Jira accepts both empty and null forms as valid ways to find issues where the field has not been populated.
The opposite condition is also important. If you want to find issues where a field does contain data you use not empty or not null variants. When you run a search such as labels is not empty Jira returns only the issues where one or more labels have been applied. This is useful when you want to find all issues that have been categorized or grouped. If you are looking for issues that have any value at all in the field you can also say labels is not null. Jira interprets both instructions to mean the user stored something in the field. Not empty and not null are both accepted and often return the same results.
Another common expression is the not equals operator. When you search for labels not equals empty you are essentially telling Jira to show every issue where the labels field is filled with something. This can be helpful when cleaning backlogs or checking whether users are applying metadata correctly. It is important to understand that not equals empty and is not empty behave very similarly because they both exclude blank fields. The difference is mostly stylistic and based on how the user prefers to phrase the query.
Behind the scenes Jira evaluates these expressions using its search index. When a query is performed Jira checks the field’s stored value, determines whether it is empty, null or populated and then returns only the issues that match the condition. This allows JQL to remain flexible and forgiving. You often see multiple variations of the same query approved as correct because Jira’s search engine treats them as equivalent. This is especially true for fields that allow more than one value such as labels or components.
JQL can feel intimidating at first but once you understand how it interprets empty and not empty conditions it becomes much easier to use. It gives you incredible control over large sets of work items and helps you maintain structure and cleanliness in your Jira spaces. Whether you are searching for issues that need categorization, validating data quality or filtering reports JQL gives you a reliable and expressive way to find exactly what you need.
Cameron McKenzie is an AWS Certified AI Practitioner,Machine Learning Engineer,Solutions Architect and author of many popular books in the software development and Cloud Computing space. His growing YouTube channel has well over 30,000 subscribers.
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