Opteryx Studio

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Opteryx Studio

Datasets

Details

Select a dataset to see its row count, columns, and partitions.

What did that query cost?

Run a query and this tab will break down the time it spent planning versus executing, the volume of data it read, and the number of rows it returned.

Reach for it when a query is slower than you expect: the split between planning and execution tells you whether the cost is in working out the answer or in reading the data to answer it.

Example details

Total time	892ms
Planning	12ms
Execution	880ms
Data scanned	340 MB
Result rows	42
Result size	3.2 KB

Planning & execution Total time splits into planning — working out how to run the query — and execution — actually reading and processing the data. A big planning number points at a complex query; a big execution number points at the data itself.
Data scanned vs. result size Data scanned is how much Opteryx had to read to answer the query; result size is how much came back to you. A scan far bigger than the result usually means most of what was read got filtered out.

How did Opteryx answer that?

Run a query and this tab will show the steps the engine took — reads, filters, joins and aggregations — as a tree, with the rows and time each step accounted for.

Each step feeds the one it is nested under, so the deepest steps run first. The step handling the most rows is usually the one worth attacking, and a filter that sits close to the read it belongs to is far cheaper than the same filter applied after a join.

Example step

INNER JOIN 8.42ms · 34%

slowest

128K rows (4.1 MB) 32K rows (980 KB)

Step name What this step is doing — reading a table, joining, filtering, sorting, and so on. The line underneath it gives the specifics: which table, which columns, which condition.
Color How costly this step was — red is the single slowest step in the query, amber still takes a meaningful share of the total time, green is comfortably cheap.
Time & share How long this step took, and what percentage of the whole query's time it accounted for.
Rows in / out Rows (and data volume) that flowed into and out of this step. A big drop means a filter did real work; a big jump means a join fanned rows out.

Click any step in a real plan to expand it and see its full detail.

Title

Chart type

Stacked

X axis

Y axis

Split by

Sort

Run a query that returns at least one numeric column, then choose what to plot on each axis using the controls to the left. Charts can be saved as an image with Download PNG.

Learn

Language reference

Query Basics

Use SELECT … FROM … to read from a dataset.

Add WHERE to filter, ORDER BY to sort, LIMIT to cap results.

Aggregate with COUNT, SUM, AVG, MIN, MAX alongside GROUP BY.

Useful Tips

Results scroll horizontally when columns exceed their minimum width.

Use the Results, Details, and Execution Plan tabs to inspect output.

Upload prepares files first; commit wiring comes later.

Function reference

ABS +

Absolute value.

APPROX_DISTINCT +

HyperLogLog distinct count.

ARRAY_CONTAINS +

Test if array contains item.

ARRAY_CONTAINS_ALL +

Test if array contains all items from set.

COUNT +

Row count.

DATE_TRUNC +

Bucket timestamp to unit.