Please use the form below to provide your feedback. Because your feedback is valuable to us, the information you submit in this form is recorded in our issue tracking system (JIRA), which is publicly available. You can track the status of your feedback using the ticket number displayed in the dialog once you submit the form.

Query Tab

  • Capella Operational
      +
      Use the Query tab to develop and run SQL++ queries from your browser.

      With the Data Tools  Query tab, you can also:

      • Explore data

      • Create, edit, and run queries

      • Save SQL++ queries

      • View and save query results

      • Explore the document structures in a bucket

      Prerequisites

      Access the Query Tab

      To open the Query tab in a cluster running the Query Service:

      1. On the Projects tab in your organization, click the project with the cluster you’re working with.

      2. On the Operational tab, select your cluster.

      3. Go to Data Tools  Query.

      The Query tab consists of three working areas:

      You can expand and collapse the Cluster Schema Browser. You can vertically resize or expand the Query Editor and Results areas accordingly when you write queries or view query results.

      Cluster Schema Browser

      The cluster schema browser (left pane) displays the buckets, scopes, and collections in the current cluster so you can browse your cluster schema. These keyspaces are in a hierarchy that you can expand or collapse.

      • To expand or collapse a heading within the hierarchy, click the heading, or click the arrow before the heading.

      Buckets appear at the top level of the hierarchy. When you expand a bucket, the scopes within that bucket appear below it. Similarly, when you expand a scope, the collections within that scope appear below it. The number of collections within the bucket is displayed to the right of the bucket heading.

      Add a Bucket, Scope, or Collection

      1. To add a new bucket, scope, or collection for your data in the cluster schema browser, click +Create.

      2. Choose New and enter a name for your bucket, scope, or collection.

      3. Click Create.

        For more information about how to create a bucket with custom settings, see Create a Bucket.

      Query Editor

      The query editor is where you build and run queries, and view query execution plans.

      The query editor provides the following additional features:

      • Syntax coloring: For easy viewing, SQL++ keywords, numbers, and string literals are differently colored.

      • Auto-completion: Enter all or part of a keyword in the query editor and press Ctrl+Space to view a list of potential matching SQL++ keywords or bucket, scope, and collection names. For names that have a space or a hyphen (-), the auto-complete option includes back quotes around the name.

      • Support for SQL++ INFER statements: Support the SQL++ INFER statement.

      Specify a Bucket and Scope Context

      You can specify the bucket and scope query context. When you set the query context to a bucket and scope, you can write queries using just the collection name without specifying the keyspace path.

      For example, here’s how a query would look without specifying a bucket and scope in the query editor:

      SELECT * FROM `travel-sample`.`inventory`.`airline`;

      If you specify the bucket as travel-sample and the scope as inventory, the query can be simplified to:

      SELECT * FROM `airline`;

      To set the query context, from Query Context, choose a Bucket and Scope from the lists.

      To remove the query context, choose select a bucket from the Bucket list.

      For more information about scopes and collections, see Buckets, Scopes, and Collections.

      Run a Query

      In the query editor, write a SQL++ query or use Capella iQ for assistance.

      Use the Format button to improve the formatting and readability of your query before running it.

      Once you have a statement ready, click Run.

      You can also execute queries by typing a semi-colon (;) at the end of the query and pressing Enter.

      When the query is running, the Run button changes to Cancel, which allows you to cancel the running query. When you cancel a running query, it stops the activity on the cluster side as well.

      The Cancel button doesn’t cancel index creation statements. The index creation continues on the server side even though it appears to have been canceled from the query editor.

      Modify Query Settings

      You can specify various settings for the query editor by clicking Query Options.

      Configure the following settings and click Save Settings to save the configuration.

      Option Description

      Collect query timings

      Collects per-operator query timings during query executions and displays them in a query plan. This option is selected by default.

      Use Cost-Based Optimizer

      Turns the cost-based optimizer on or off. For more information, see Understand the Cost-Based Optimizer for Queries.

      Don’t save query history

      Disables auto-saving query history to local storage in your browser. This is a consideration for shared machines. When selected, any query history will be lost when you leave or refresh the query editor.

      Max Parallelism

      Specifies the maximum parallelism for the query. If you do not specify, the cbq-engine uses its default value. For more information about maximum parallelism, see the max_parallelism request-level parameter.

      Query Timeout

      The timeout parameter in seconds limiting the running time of a query. You can set this to a maximum of 1800 seconds

      Transaction Timeout

      Specifies the maximum time in seconds spent on a transaction before timing out.

      Scan Consistency

      This is a cbq-engine option. Select one of the following options:

      • Not Bounded

      • Request Plus

      • Statement Plus

      For more information, see Index Consistency.

      Positional Parameters

      For the prepared queries, this option allows you to specify values for $1, $2, and so on up to as many positional parameters as you have. Click the + button to add new positional parameters, and the - button to remove the parameters. The parameters are automatically labeled as "$1", "$2", and so on.

      Named Parameters

      For the prepared queries, this option allows you to specify any number of named parameters. Click the + button to add new named parameters, and the - button to remove the parameters. Named parameters must start with the dollar sign ($) for use in prepared queries. Otherwise, they are interpreted as parameters to the Query REST API.

      Index Advice

      The ADVISE command generates index advice to recommend indexes that optimize the response time for a query. You can use this command with SELECT, MERGE, UPDATE, or DELETE queries.

      • To view index advice for a query entered into the query editor, click Index Advice. The query editor shows any suggested indexes by name and keyspace.

      • To view updated advice after you change a query, or filter available indexes by bucket, scope, or collection, click Update Advice.

      Query Results

      When you execute a query, the results display in the query results area. Since large result sets can take a long time to display, it’s recommended that you use the LIMIT clause as part of your query when appropriate.

      When a query finishes, metrics for that query appear between the query editor and the query results areas.

      Query Metric Description

      The status of the query

      The values can be success, failed, or HTTP codes.

      Last Run

      The time at which the query was last executed.

      Round-trip time (RTT)

      The total time it took to send the request and receive the response from the server.

      Docs

      The number of documents returned.

      Size

      The total size, in bytes, of the documents returned.

      Elapsed

      The time taken by the server to process the request.

      Execution

      The time taken by the server to execute the query.

      Table Format

      The Table tab presents the results in a tabular format. The tool converts the JSON documents to HTML tables and presents sub-objects or sub-arrays as sub-tables. This format works well for queries that return an array of objects, like select `beer-sample`.* from `beer-sample`;. Point to a data value to see the path to that value in a tooltip. You can sort the data based on a column by clicking the column header.

      JSON Format

      The JSON tab formats the results to make the data easy to read. You can also expand and collapse objects and array values using the small arrow icons next to the line numbers.

      Chart Format

      You can click Chart to present the results as a chart, as long as your query returns a suitable data series.

      You can select the type of chart and the data options from the drop-down controls at the top left of the chart. You can select the type of chart and the data options from the lists at the top left of the chart. To select the type of chart, in the Chart Type list, select a format for the chart: X-Y, Connected Points, Line, Area, Bar, Grouped Bar, Pie, or Donut.

      iQ Insights Format

      The iQ Insights tab lets you leverage the power of AI to generate charts and graphs based on your query results. You can choose from different visualizations generated by AI and select those that best represent your data.

      For more information about iQ Insights, see Explore Capella iQ Insights.

      X-Y, Connected Points, Line, and Area Charts

      1. In the X-axis column list, select the field for the x-axis of the chart.

      2. In the Y-axis column list, select the field for the y-axis of the chart.

      For X-Y charts only: in the Color list, select a color for the data points.

      Bar, Grouped Bar, Pie, and Donut Charts

      1. In the Label list, select the field to use to categorize the data.

      2. In the Value list, specify the data series to be rendered on the chart.

      Plan

      Each time you execute a query, an EXPLAIN command is automatically run in the background to retrieve the query plan for that query.

      Plan

      The Plan tab presents the query in a graphical format.

      At the top, the tab shows a summary which also shows lists of the buckets, indexes, and fields used by the query.

      At the bottom of the tab is a data-flow diagram of query operators, with the initial scans at the right, and the final output on the left.

      Potentially expensive operators are highlighted.

      The data flow generally follows these steps:

      1. Scan

      2. Fetch

      3. Filter

      4. Projection (part 1)

      5. Order

      6. Projection (part 2)

      Projection is split into two parts (one before Order and one after Order), but the query editor shows only the first part.

      Click a unit of the plan to see more details about it.

      An example query:

      Unit name Information shown when clicked

      Order

      		 
      {'#operator':'Order':'sort_terms':
[{'expr':'(`travel-sample`.`name`)'}]}

      Project

      		 
      {'#operator':'InitialProject':'result_terms':
[{'expr':'self','star':true}]}

      Filter

      		 
      {'#operator':'Filter','condition':'(((`travel-sample`.`type`) = \'landmark\') and
((`travel-sample`.`city`) = \'San Francisco\'))'}

      Fetch

      		 
      {'#operator':'Fetch','keyspace':'travel-sample','namespace':'default'}

      IntersectScan

      (none)

      IndexScan2 (above)

      		 
      {'#operator':'IndexScan2','index':'def_city','index_id':'d51323973a9c8458','index_projection':
{'primary_key':true},'keyspace':'travel-sample','namespace':'default','spans':
[{'exact':true,'range':[{'high':'\San Francisco\'','inclusion':3,'low':'\'San Francisco\''}]}],'using':'gsi'}

      IndexScan2 (below)

      		 
      {'#operator':'IndexScan2','index':'def_city','index_id':'a11b1af8651888cf','index_projection':
{'primary_key':true},'keyspace':'travel-sample','namespace':'default','spans':
[{'exact':true,'range':[{'high':'\'landmark'\'','inclusion':3,'low':'\'landmark\''}]}],'using':'gsi'}

      In general, the preference of scan is

      1. Covering Index

      2. Index Scan

      3. Intersect Scan

      4. Union Scan

      5. Fetch

      Plan Text

      The Plan Text tab shows the EXPLAIN query execution plan in JSON format.

      View Query History

      The query editor maintains a history of all the queries executed.

      If you edit a previous query and execute it, the new query is stored at the end of the history. The history is persistent across browser sessions. The query history saves queries; due to limited browser storage, it doesn’t save query results. When you restart the browser or reload the page, you can see your old queries, but you must re-execute the queries if you want to see their results.

      Clearing the browser history clears the history maintained by the query editor as well.

      To open the Query History menu, click History .

      You can scroll through the entire query history, and click an individual query to view that particular point in the history.

      • Search history: You can search the query history by entering text in the Filter saved queries search box. All matching queries are displayed.

      • Delete a specific entry: Click the Trash icon next to a query to delete it from the history.

        Deleting entries can be useful if you want a more manicured history when you export the history for future use.

      • Delete all entries: Click the Trash icon next to the Export query history icon to delete the entire query history.

      Import Queries

      You can load a new query history into the query editor from a JSON file. The query history can be the exported query history from a different cluster.

      Importing a query history overwrites your current query history.

      1. From the cluster’s Data Tools  Query page, click History.

        This opens the Query History menu.

      2. Click the Import query history icon next to the search box.

      3. From the Open file window choose a local .json file that you want to import.

      4. Click Open.

        The preexisting query history is overwritten with the query history of the imported file.

      Export Query History

      You can export the current query history to a JSON file, which you import into other clusters.

      1. From the cluster’s Data Tools  Query page, click History.

        This opens the Query History menu.

      2. Click the Export query history icon next to the search box.

        This opens the Export Query History window.

      3. Use the File Name field to specify a name for the exported JSON file.

      4. Click Submit.

        The window closes and the file downloads to your computer.