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6 docs tagged with "Stream Data"

Time series and streaming data retrieval, aggregation, and downsampling

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Aggregation Queries

Aggregation queries compute summary values (averages, totals, extremes) across time-series data points instead of returning individual rows. Use these when you need calculated metrics rather than raw data — for example, the average voltage over the last hour or the total energy produced per machine.

Downsampling Query

A downsampling query reduces the density of time-series data by dividing a time range into equal-sized buckets and applying an aggregation function to each bucket. This is essential for visualizing large datasets on dashboards and charts — instead of transferring thousands of raw data points, you get a manageable number of summarized values.

Persisted Queries

Persisted queries are saved query definitions stored as runtime entities. Instead of specifying all query parameters every time, you create a query definition once and execute it by its rtId. This is useful for dashboard widgets, recurring reports, and any scenario where the same query needs to be executed repeatedly.

Simple Query

A simple query retrieves raw time-series rows from CrateDB. You choose which columns to return and can apply filters, sorting, and time range restrictions. This is the most fundamental stream data query type — use it when you need individual data points rather than aggregated summaries.

Stream Data Archives

A Stream Data Archive is the unit of configuration and storage for time-series data in OctoMesh. Each archive is a versioned, typed, per-tenant CrateDB table that captures a curated set of attribute paths from a Construction Kit type. Archives have a strict lifecycle (Created → Activated → Disabled / Failed), an immutable schema once activated, and a three-tier activation gate (instance → tenant → archive) that determines whether the data plane is open.

Stream Data Archives

The Stream Data Archives section of the Refinery Studio lets you create and manage the time-series archives that capture data into CrateDB. Each archive defines a CK type, a curated list of attribute paths, and a status — and the studio walks you through every state transition (Activate, Disable, Enable, Retry, Delete) with confirmation dialogs.