- Troubleshooting guide
- Improve Looker Studio performance
- Hyperlinks in data
- What does the "Unable to aggregate ratio metrics" error mean?
- Example reports
- Missing data
- Graph negative numbers
- Filter by multiple email addresses per row
- Resolve invalid field name errors
- How to add more than 10 AND/OR filters to a chart
-
Troubleshooting guide
If you experience an issue with a chart, report, or data source, check this guide to see if it's listed. If your issue is listed, click Steps to resolve to learn how you might further investigate and fix the problem.
In this article:Basic hygiene steps
Some issues with Looker Studio can be caused by temporary network errors or backend glitches. Try these basic hygiene steps before you spend a lot of time troubleshooting a problem. After you try each step, check to see if the issue is resolved.
Possible symptom and error messages
Error messages are shown in
green code font
.- Unresponsive pages
System error
-
Looker Studio is not available
Steps to resolve
- Refresh the browser window.
- Clear your browser cache and cookies.
- Restart your browser.
- Try using a different browser.
- Restart your computer.
- Try using a different computer, if possible.
If these steps don't solve the issue, wait a bit, and then check again. If the problem persists, you can see if other users are experiencing the same issue by searching on the Looker Studio Community forum.
Access issues
If you are a Google Workspace or Cloud Identity customer, your organization's administrator must enable Looker Studio before you can use it.
Possible error message
Error messages are shown in
green code font
.We are sorry, but you do not have access to this service. Please contact your Organization Administrator for access.
Steps to resolve
Have your organization's administrator enable Looker Studio for your organization. Learn more about Looker Studio's enterprise features.Connection issues
Data connection issues can occur for several reasons. Some issues are expected, such as when you don't have the proper data credentials to view the data in a data source that's been shared with you. Other reasons include broken or incomplete configurations, deleted data sources, loss of authorization to the data, and so on.
Try these steps to resolve problems connecting to your data set.
Possible error messages
Error messages are shown in
green code font
.Missing data source
Data set configuration error
No data set access
Data source not attached
Data source needs to be added
The underlying data has changed
Database connection error
Steps to resolve
- Edit the broken component and then add the correct data source.
- Refresh the data source fields
- Reconnect the data source.
- Remove the data source(s) from the reports, and then add them back.
- Create a new data source to see if that works.
- Revoke and then restore Looker Studio's access to your Google account.
Chart configuration issues
Charts with incomplete or incompatible chart configurations will display errors.
Possible error messages
Error messages are shown in
green code font
.System error
Chart configuration incomplete
Invalid combination of metrics and dimensions
Steps to resolve
- Fix or remove any invalid calculated fields.
- Choose different fields for the chart.
- Refresh the data source fields.
- Reconnect the data source.
About the
Invalid combination of metrics and dimensions
errorThis error occurs when the chart tries to visualize data in a way that's not supported by the data source. This is a limitation of some backend systems, such as Google Analytics and Google Ads, where the data is stored in a fixed structure that only allows certain fields to be queried together.
Tip: For Google Analytics data, you can use the Dimensions and Metrics Explorer to find compatible fields.User interface and functionality issues
If Looker Studio suddenly stops working or otherwise misbehaves, incompatible extensions or add-ons could be causing the problem.
Possible symptoms and error message
Error messages are shown in
green code font
.- Features not working
- Missing UI elements
- Product stops responding
Sorry! We can't save this report right now.
Steps to resolve
- Try the basic hygiene steps described previously on this page.
- Try a different browser.
- Disable browser extensions / add-ons.
If disabling all extensions solves the issue, try adding the extensions back in one at a time until you find out which one is causing the issue (and then consider posting your discovery on the Looker Studio Community forum).
Blending issues
The most common issues people experience with blends can be put in the following buckets:
- Misconfigured joins
- Missing or incorrect data source connections
- Issues with / confusion over the blend results
Misconfigured join example symptom and error messages
Error messages are shown in
green code font
.One or more join configurations is incomplete.
One or more join configurations is missing a join condition.
Join key incomplete. Each selected data source must specify a join key field for every join key.
- Pink "Missing" field in the join condition.
Steps to resolve
- Edit the join configuration.
- Make sure each configuration in the blend has a join condition and join operator (unless you're using a cross join, in which case no join condition is allowed).
- For missing fields: either remove the field, or make sure that each pair of join configurations has a corresponding field.
Missing or incorrect data source connection example error message
One or more tables is missing its data source.
Steps to resolve
Reconnect any tables that are missing their data source.Google Analytics 4 quotas exceeded
Beginning November 7, 2022, Looker Studio reports that connect to Google Analytics 4 data are subject to Google Analytics Data API (GA4) quotas. You can monitor your report's GA4 data usage via the Google Analytics Token Usage dialog.
View token usage
- Edit your Looker Studio report.
- To see your report's overall token usage, right-click the report canvas, then choose Google Analytics token usage.
- To see the token usage for a specific component, right-click the component, then choose Google Analytics token usage.
For the overall usage of Google Analytics 4 tokens, you can view:
- The number of quota tokens used by the entire report or per page for the current user session
- The number of quota tokens remain available before the quota is reached
- The number of quota tokens are consumed by each chart, sorted by those that use more tokens
For token usage by a specific component, you can view:
- The number of quota tokens have been consumed by each request
- The time that each request finished
- Whether the request was served from the underlying dataset or from memory, where a red X indicates that the request was served from the dataset while a green checkmark indicates that the request was served from memory. See the Manage data freshness article for more information.
Quota exceeded error messages
Reports that exceed these quotas may display one of the following error messages:
Exhausted concurrent requests quota. Please send fewer requests concurrently.
This property has issued too many requests in the last day.
Too many requests using this Google Analytics property have encountered errors in the last hour.
This property has issued too many requests in the last hour.
This property is denied access to Google Analytics.
This property has issued too many potentially thresholded requests in the last hour.
This project/property has issued too many requests in the last hour.
Steps to resolve
If you experience this error, you have the following options to reduce the amount of data that is queried from Google Analytics 4. These steps can help avoid quota hits by increasing reliance on the Looker Studio data caching mechanism:
- First, use owner's credentials for the data source instead of viewer credentials to increase the likelihood of using cached data instead of querying data and using quota tokens. If you are relying on viewer's credentials, consider switching to owner's.
- If your reports use multiple Google Analytics 4 data sources, consider consolidating them if possible into a single reusable data source. This will also increase the likelihood of using cached data instead of querying data and using tokens.
- Reduce the traffic to the report. Consider sharing the report with fewer people, and don't embed the report in a high traffic website.
- Reduce the number of charts on each page.
- Extract the Google Analytics 4 data and use the extracted data instead of the Google Analytics 4 data source.
- Note: you'll need to wait until any exceeded quotas have refreshed before you can extract the data. Depending on the quota exceeded, this can take up to 24 hours.
- Export your Analytics data to BigQuery, then use the BigQuery connector to visualize that data in Looker Studio.
- Upgrade to Analytics 360.
- Consider using a partner connector.
Strategies for troubleshooting more complex issues
When you're trying to diagnose less obvious problems with Looker Studio, the first step is to identify where the problem is occurring.
For example, is the problem generalized, or is it restricted? Is it a problem with all your reports, or a specific report? Does it happen with every component type, or only with a specific component? Does the issue appear in multiple browsers or only in a specific version of a specific browser?
See also: What you need to use Looker Studio
The next step is to reduce the number of variables.
Generally, this means trying to isolate the problem to the fewest possible factors, by minimizing the data or simplifying the report. For example, if you suspect a problem with the data, try to use filters or edit the data set to reduce the number of rows by half. If the problem goes away but reappears when you include the other half of the rows, then you'll know the issue is somewhere in that second half of the data.
Similarly, if the problem is with a specific chart, first try creating a simple version of the chart with the minimum number of fields and simplest style options, and then gradually increase the complexity to see if the issue is caused by a specific field or setting.
Report a problem to Google
If you can't resolve the problem, you can report it to Google. To help us diagnose the problem, please be ready to provide the following information:
- A complete description of the problem
- Steps to reproduce the problemc
- Any error messages or error IDs that appear
- A link to a test report or data source that demonstrates the problem
About error IDs
If you see an error ID (typically an 8-character long mix of numbers and letters), be sure to include it in your report to Google. Error IDs are unique identifiers that help our engineers to quickly find the error in our logs. Rather than mapping statically to a specific error condition, error IDs are dynamically generated so they correspond to a particular instance of the error. This means that the IDs will change each time the error occurs.About test reports
As noted in the Strategies for troubleshooting more complex issues section, reducing the complexity of the test reports you share makes it easier for us to troubleshoot. If possible, the test report you create should be as simple as possible. For example, make a copy of the original report, then remove extra pages, charts, filters, and other components that aren't required to demonstrate the problem.
-
Improve Looker Studio performance
The speed with which a Looker Studio report loads and responds to viewer changes, such as applying filters or changing the date range, depends on a number of factors, which include the following:
- the performance of the underlying dataset
- the amount of data that is being queried by the visualizations in the report
- the complexity of those queries
- network latency
Some of these factors are beyond your (or Looker Studio's) ability to control. For example, there may not be much you can do to improve the responsiveness of the underlying data platform or speed up your network connection. There are, however, some things that you can do to fine-tune your report performance in Looker Studio.
Tip: Performance tuning can involve tradeoffs between speed and responsiveness on one side, and up-to-date data and user customization on the other. The tips offered here may not be appropriate for every customer's use case.Adjust the data freshness rate
Most data source types have a data freshness option (the exception to this is extracted data sources). This option lets you balance your need for up-to-date information against report performance and potential query costs or quotas. Each type of data source has its own default data freshness threshold, but you can adjust this threshold as needed. For example, if you are measuring ad performance on your site or app, you might find that daily data updates are sufficient. Reports that are based on social media analytics, on the other hand, may need their data updated multiple times a day.
Learn more about managing data freshness.
Use an extracted data source
An extracted data source is a static snapshot of up to 100 MB of data. Once created, data requests from your report go to this snapshot, not to the underlying dataset. Using an extracted data source can make your reports and explorations load faster and be more responsive than when working with a live connection to your data.
Extracted data sources don't have a data freshness option. Instead, you can schedule when you want to the data in the extracted data source to update.
Learn more about extracting data.
Accelerate BigQuery data sources with BI Engine
BigQuery BI Engine is a fast, in-memory analysis service. By using BI Engine you can analyze data stored in BigQuery with sub-second query response time and with high concurrency.
BI Engine integrates with Looker Studio to accelerate data exploration and analysis. With BI Engine, you can build rich, interactive dashboards and reports in Looker Studio without compromising performance, scale, security, or data freshness.
-
Hyperlinks in data
You can display clickable links in your data using a table. There are 2 ways to get these links:
- Directly from your data set, using the URL field type
- Generating the link using the HYPERLINK function
URL field type
When you create a data source, Looker Studio will detect valid URLs in the data set and assign the URL field type to that dimension. (If Looker Studio doesn't detect the URLs automatically, you can set the field type to URL manually.)
URL fields display the full link in charts. In tables, this link is clickable.
HYPERLINK function
The HYPERLINK function lets you construct links in calculated fields. The HYPERLINK function takes a URL and a link label as input. The output is a clickable link when displayed in a table (in other charts, the link text is not clickable).
Only certain protocols are supported in both URL fields and the HYPERLINK function. See the HYPERLINK article for details.
-
What does the "Unable to aggregate ratio metrics" error mean?
At a glance
Have you seen this error message?
Unable to aggregate ratio metrics in the request. Please select another metric.
This error means you've asked Looker Studio to do something with an already aggregated ratio metric that it can't do. For example, you've applied a filter based on a calculated field to a chart that contains a ratio metric.
The solution is to select a non-ratio field in the chart (e.g., use Impressions instead of CTR), or remove or change the filter.
In this article:In depth
Ratio metrics show the relative sizes of two or more values. For instance, the Google Ads metric, e.g. Clickthrough rate (CTR) is the number of clicks that your ad receives divided by the number of times your ad is shown. In Google Analytics, Bounce Rate is single-page sessions divided by all sessions, while Entrances / Pageviews calculates the ratio of visitors entering your site and beginning a new session compared to the number of pageviews.
In Looker Studio, you get the error above when you filter a chart that includes ratio metrics in a way that requires the product to recalculate the ratios.
Here are 3 things to help you understand this issue:
1) Data from data sets such as Google Analytics, Google Ads, YouTube, and Google Marketing Platforms products is already aggregated by the time it gets to Looker Studio. For example, when Looker Studio requests a Google Ads metric such as CTR (click-through rate), the data is already processed into the appropriate aggregation type.
2) Because of the above, calculated field functions are applied to your data post-aggregation. It's not possible (nor would it generally make sense) to go back into the raw data and look at every unique instance of that metric. For example, if you try to create a calculated field with the formula
SUM(Impressions)
in a Google Ads data source, you'll get the error:Re-aggregating metrics is not supported
.That's because Impressions is already aggregated (and its aggregation type, Auto, can't be changed).
Note that this isn't necessarily the case with data sources such as Google Sheets, MySQL, or BigQuery, where you are able to send non-aggregated data to Looker Studio. For example, if you had raw impression data in a Sheet, you could use the SUM function to add it all up, the AVG function to generate the average, etc.3) For consistency, all calculated field functions in Looker Studio are available for use with all data source types, even if the underlying system doesn't natively support that function. For example, you can use the CONCAT function to join multiple values in any data source, even if the underlying system doesn't have a CONCAT function of its own. Instead of "pushing down" the CONCAT function to the underlying system, Looker Studio requests the data and performs the concatenation itself.
Aggregation failure example
So what does all that have to do with the "
Unable to aggregate ratio metrics
" error? Let's go a little deeper with the CONCAT example to find out.Suppose you create a calculated field called Campaign : Click Type in a Google Ads data source, using the following formula:
CONCAT(Campaign, " : ", Click Type)
Looker Studio issues queries for Campaign and Click Type individually, and then performs the concatenation. The results are grouped, so there is no duplication of records.
You can now use that concatenated field in your charts, and the metrics you include are aggregated properly. For example, we could use Campaign : Click Type as the dimension and CTR as the ratio metric in a table:
But now, let's say you apply a filter to show only those records where the Click Type is
Headline
:This will break the chart:
Why it breaks
The filter asks Looker Studio to include each record returned by the Campaign : Click Type if it contains "Headline." That field is a concatenation of 2 dimensions: to fulfill this request, Looker Studio has to refetch those dimensions, and then apply the filter. The problem is the presence in the table of the ratio metric, CTR. Google Ads ratio metrics are computed before Looker Studio requests them. Looker Studio has no way to access the raw data and recompute the new ratios for the records that just contain "Headline" in the concatenated field.
The solution
The solution in cases like this depends on the data you are trying to show. In this example, you could either replace the CTR metric with a non-ratio metric, such as Impressions. Or, instead of filtering on the concatenated Campaign : Click Type field, put the filter on just the standard Click Type field, which would achieve the same result.
The chart now works:
Related resources
-
Example reports
Example reports:Report Audience Welcome to Looker Studio! (Start here)
Learn how to view, edit and create a Looker Studio report.
New users Filter Control Example
This report illustrates various styles of filter controls. The data comes from two sources, Google Sheets and Google Analytics . The filter controls at the top of the report show how various filter control configurations work.
All users Data coloring example
This report demonstrates 2 ways to color your data:
- Color by the dimension value. E.g., "France" is always represented in red. This is the default behavior for new reports.
- Color by the order of the dimension data. E.g., the first series is always blue.
All users Design reports using the layout grid
This report illustrates using adjustable grid sizes to achieve a more standardized report design.
The minimum canvas grid size is 10 px. You can adjust this with the Grid Settings options. Increasing the grid size makes it easier to layout your charts, controls, and other components.
This report includes a Google Analytics data control. You can use it as a template for your Analytics data.All users Running calculations
Running calculations compute summary results for each record of data, helping you see how each contributes to the whole picture.
All users Understand report-level component position
Question:
Why do my report-level components disappear?
Solution:
Change Report-level Component Position to "Top."
All users Reverse Axes
This report demonstrates controlling the X and Y axis direction in Cartesian charts.
All users Data blending example: classes, students, grades
This demonstration report illustrates how to interpret and visualize your data to answer questions about your business when that data lives in separate data sources. For example, a school administrator might want to look for insights concerning students, the classes they've enrolled in, and the grades those students received.
Advanced users Lat, Long, and City Name in Geo charts
Question:
How can I use latitude and longitude in a Geo chart to provide maximum resolution in my data, but still see city names in the chart?
Solution:
Use a calculated field to combine latitude and longitude with the city name. Example: CONCAT(Lat Long , "(", City,")")
Advanced users HYPERLINK Example
This report demonstrates the Hyperlink field. Hyperlinks create clickable links in tables.
To create a Hyperlink field, use the
HYPERLINK
function, and provide a URL as the first parameter, and a Text field, or formula that returns Text, as the secondHYPERLINK
parameter.Advanced users Image Link Example
This report demonstrates the Image Link field. Image Links create clickable images in tables.
To create an Image Link field, use the
HYPERLINK
function, and provide a URL as the first parameter, and an Image field, or an IMAGE function with a valid link to an image, as the secondHYPERLINK
parameter.Advanced users -
Missing data
If your reports or data sources aren't showing all the information you expect, check the following:
Missing data in reports
Is the data out-of-date?
If the report is missing some recently added data, try refreshing the report data.
Note: You must be an editor of the report to refresh the data.
Is the data filtered?
Edit the report, then click Resources > Manage Added Filters to see if there are any filter properties in the report. If there are, check their setup to make sure that's not the cause of the missing data.
Missing fields in data sources
Is the data source out of sync with the dataset?
If the data source is missing some recently added fields (columns), try refreshing data source fields.
Is your Google Sheets data source missing rows or columns?
If the rows (data) or columns (fields) of your Sheets data source are still not appearing after refreshing the fields as described above, make sure the data source connection includes the proper range and options. You must be the owner of the data source to do this.
- Edit the data source.
- On the left, click EDIT CONNECTION.
- Review the connection options, on the right. Be sure any specified range includes all your data, and that you are including hidden and filtered fields, if appropriate.
Sheets connector options.
Is it a connector limitation?
Connectors that are based on fixed schemas, which include many of the Google product connectors, may not deliver all the fields of the underlying dataset. If your data source appears to be missing fields that you know are in the original product, it's possible that field is not supported in Looker Studio. You can check the issue tracker to see if the field has already been requested, or if not, file a feature request.
-
Graph negative numbers
As of 2019-01-16, the default value for Axis min is (auto), so you'll only need to change this for older charts.
Previously, the default Axis min setting was "0."
To display metrics with negative values in a chart, set the Axis min option to (auto):
- Edit your report.
- Select the chart.
- Select the STYLE panel.
- Locate the main axis settings: for default charts, this will be the left axis, but could also be right or bottom, depending on how you've customized your chart.
- Change the Axis min value to (auto) by deleting the current setting.
Here's an example of how charts look with Axis min 0 versus Axis min (auto):
- Data in the top charts contains mixed negative and positive values.
- Charts on the left are set to use Axis min: 0.
- Charts on the right use Axis min: (auto).
- Note how the last two dimension values ("Green" and "Blue") appear in the charts.
- Data in the middle charts only contains positive values. In this case, there is no difference between 0 and (auto) settings.
- Data in the bottom charts only contains negative values. Here, using the (auto) setting on the right provides the correct visualization.
-
Filter by multiple email addresses per row
Prerequisites
This solution relies on the following concepts / tasks in Looker Studio:Filtering by email address works by comparing the address of the logged in viewer to a field in your data source that contains valid email addresses. For each row in your data, the filter checks to see if the viewer's email matches the address in that row.
Consider the following data:
Email Data alan@example.com abc mary@example.com cde alan@example.com efg mary@example.com ghi If this data was filtered by email address, and alan@example.com viewed the filtered report, he'd only see the data
"abc" and "efg." If mary@example.com viewed the same report, she'd see the data "cde" and "ghi."This is fine if you have a 1:1 relationship between viewers and the data. But what if you wanted also wanted manager@example.com to see the data? That is, you want many people to see the same rows of data. (This is known as a many:many relationship.)
Filter by email only works on one address per row, so you can't simply put a list of addresses in your email field. For example, this won't work:
Email Data alan@example.com, manager@example.com, vp@example.com, bigwig@customer.com abc Solution: Use data blending
You can create a many:many relationship between email addresses and your data by blending a table of addresses with your data, using any common field as a join key.
Fruit stand example
You manage a produce company, and want show your sales representatives how they are performing at the various fruit stands they service. Multiple sales people can service multiple stands. To filter the data so your sales people only see their data, you could do the following:
Step 1: Create an access control list table
In this step, you'll create an access control list (ACL) table that contains the email addresses of the authorized sales people, paired with a data field (a fruit stand name) that can be used as a join key in the blend.
Sales Rep Email Join key salesrep1@example.com Fruit Stand A salesrep2@example.com Fruit Stand A salesrep1@example.com Fruit Stand B salesrep2@example.com
Fruit Stand C Access control list (ACL) table
Note that salesrep1 can see data for Fruit Stand A and Fruit Stand B, while salesrep2 can see data for Fruit Stand A and Fruit Stand C.
Step 2: Create the data table
The data table tracks the sales each representative made to each fruit stand.
Note that this table doesn't need to have the sales rep's email addresses, only the same values as in the join key (the fruit stand name). Also note the name of the join key field is not relevant: blending joins based on the data, not the field name.Fruit Stand Fruit Sales Fruit Stand A Apple 50 Fruit Stand A Banana 26 Fruit Stand A Orange 20 Fruit Stand A Pear 93 Fruit Stand B Apple 98 Fruit Stand B Banana 86 Fruit Stand B Orange 7 Fruit Stand B Pear 85 Fruit Stand C Apple 21 Fruit Stand C Banana 61 Fruit Stand C Orange 3 Fruit Stand C Pear 78 Data table
Step 3: Apply the email filter to the ACL table
Edit the data source for the ACL table and choose the Sales Rep Email field as the filter.
Step 4: Blend the ACL table with the data table
Finally, blend the data table with the ACL table. Since we want to effectively add the sales rep email as a column to the data table, we will start from the data table and then left-join the ACL table.
With no email filter applied, you'll see all the records for both sales representatives. However, with the email filter applied, blending the ACL table with the sales data table filters that data according to which sales person is viewing the report. Here's what each representative would see when they view the report:
Sales Rep 1 sees this:
Data Fruit Sales Fruit Stand A Apple 50
Fruit Stand A Banana 26
Fruit Stand A Orange 20
Fruit Stand A Pear 93
Fruit Stand B Apple 98
Fruit Stand B Banana 86
Fruit Stand B Orange 7
Fruit Stand B Pear 85
Sales Rep 2 sees this:
Data Fruit Sales Fruit Stand A Banana 26
Fruit Stand A Orange 20
Fruit Stand A Apple 50
Fruit Stand A Pear 93
Fruit Stand C Banana 61
Fruit Stand C Orange 3
Fruit Stand C Apple 21
Fruit Stand C Pear 78
-
Resolve invalid field name errors
Problem
A chart in your report displays an "Invalid field name error."
Why it breaks
Certain connectors support characters in their field names that Looker Studio is unable to process. For example, Looker Studio does not handle BigQuery fields that contain Unicode characters and special characters like ampersands, colons, and so on.
Learn more about BigQuery flexible column names.
Solution
To resolve this issue, rename the fields from the underlying dataset and then reconnect the data source.
-
How to add more than 10 AND/OR filters to a chart
Prerequisites
This solution relies on the following concepts / tasks in Looker Studio:When creating a filter on a chart, you can add
AND/OR
conditions. However, once you've added more than 10OR
conditions, you cannot add any moreOR
clauses unless you create a newAND
condition.There are a few ways to work around this limitation:
Update the filter conditions to another type
One way to work around this limit is to change your filter conditions to a more inclusive filter type.
For example, if you want a field to match 11 possible values, you can use the
IN
filter type and list each of those values.As another example, consider a field with product names. You want to create a filter that returns all products that start with the 12 letters A-L. You can achieve this with a RegExp Match type filter by using the appropriate regular expression syntax. In this example, the syntax would be the following:
REGEXP_MATCH(field, "^[A-L].*")
Move the filter conditions into a new field
Another workaround is to move the conditions into a separate calculated field and filter on that new field. Calculated fields don't have the same limit on the number of logical conditions that can be included.
For example, let's say you have 11 different fields, and you want to create a filter that checks if any of them contains a specific error string.
You can create a new field that has the 11 OR conditions that you'd need to check this condition. The formula would look like this example:
CONTAINS_TEXT(log_field_1, "error")
OR
CONTAINS_TEXT(log_field_2, "error")
OR
CONTAINS_TEXT(log_field_3, "error")
OR
CONTAINS_TEXT(log_field_4, "error")
OR
CONTAINS_TEXT(log_field_5, "error")
OR
CONTAINS_TEXT(log_field_6, "error")
OR
CONTAINS_TEXT(log_field_7, "error")
OR
CONTAINS_TEXT(log_field_8, "error")
OR
CONTAINS_TEXT(log_field_9, "error")
OR
CONTAINS_TEXT(log_field_10, "error")
OR
CONTAINS_TEXT(log_field_11, "error")
This formula field will create a Boolean field type, which evaluates to
True
orFalse
.Finally, create a filter that filters on this new field being
True
.