by Xonai

See where your Spark jobs
can perform better.

Xonai Compatibility Radar reveals how much of your Spark workload could run faster — using the event logs you already have.

One plug-and-play JAR
Read-only analysis
Secure by design
Results in minutes

Seconds for most teams.
Never hours.

Typical Runtime
< 1 min
For most real workloads
Runs locally, no waiting
Larger workload
Couple of minutes
For ~500 large applications — just like your coffee break.
📏
Analyse as much or as little as you want. There are no restrictions on log file size, number of applications, or workload complexity. A thousand applications or three logs and a hunch — both are valid places to start.

Your data stays
inside your infrastructure.

Security always comes first. Xonai Compatibility Radar does not interact with your jobs, does not access your data, and does not transmit anything outside your environment.

Data scope
Event logs.
Read-only.

Xonai Radar analyses your Spark event logs in read-only mode. It only inspects which operators ran and how long they took. It never touches the underlying datasets your jobs processed.

Execution model
No external
calls.

Xonai Radar runs locally as a standalone Java process. It does not call external services or send telemetry — nothing leaves your infrastructure.

Input & output
You control the paths.

Choose where the event logs live and where the report lands. Local filesystem, S3, GCS, or HDFS — all supported.

👀
The report lands in your hands first. The output is plain CSV and a text list: no source data, no query results, only compatibility analysis.

Not a benchmark.
A go / no-go signal.

Xonai Compatibility Radar doesn't measure speedups. It shows whether a pilot is worth running.

What it measures
Compatibility coverage, not acceleration

Xonai Radar maps your workload against what Xonai covers — and shows how much of your SQL time falls within it.

Actual runtime improvements come from running a pilot on live jobs.

What happens after
You send the report. We get on a call.

Share the output at radar@xonai.io and the engineer who built Xonai Accelerator reviews your report with you directly.

You will see which operators are supported, what falls outside, and what that means for your workload specifically.

🎯
The closer to your real workloads, the more reliable your go / no-go signal.
You can run Xonai Radar on any logs — synthetic benchmarks, sample exports, or live production records. For an outcome that gives you confidence to move forward, use logs closest to production.

Two files in plain text.
Nothing hidden.

Xonai Compatibility Radar writes two output files with coverage metrics and operator-level detail. Fully transparent and quick to validate.

App ID Total Task Time SQL Task Time Supported Task Time Coverage
1772030747255 33 min 30 s 30 min 29 s 28 min 19 s 84% covered
1772030748601 1 h 59 m 31 s 1 h 44 m 42 s 1 h 36 m 41 s 92% covered
1772030749334 4 min 50 s 3 min 21 s 2 min 53 s 86% covered
ℹ️
This page covers the essentials — for a breakdown of all fields, values, and the full output format, see Xonai Radar’s GitHub documentation →

From event logs to
a clear decision.

Step 01
Get it from GitHub

Open-source, runs anywhere.
No setup overhead.

Step 02
Run it

Point the tool at the event logs.
Results are typically ready in seconds.
Send the report to radar@xonai.io.

Step 03
We review it together

On the analysis call, your dedicated Xonai engineer turns it into a clear view of impact and next steps. That's where the numbers become meaningful.

Below the query:
Execution layer.

The SQL you write is only the starting point. The tool analyses what Spark actually ran — the physical execution plan.

01 — Input
Your Spark event logs

Reads standard Spark event logs — from development, staging, or historical production workloads.
No access to underlying datasets.

03 — Output
Compatibility coverage report

Shows how much of your query runtime Xonai can accelerate.
Review it with your dedicated engineer on a call — so you can determine if a pilot is worth running.

A lower bound.
Real gains tend to be higher.

All-or-nothing evaluation
Any unsupported operator pulls the whole group out
Event logs show the total runtime of the pipeline — not how that time is distributed between individual operators.
Supporting 3 out of 4 operators therefore does not mean accelerating 75% of the pipeline.
⚖️
The conservative rule
If any operator in the stage is unsupported, the entire pipeline is treated as unsupported.
We're Open Source
Written by hand. Not a line of AI.

Xonai Compatibility Radar is fully open-source and lives on GitHub. We wrote every line ourselves — no AI coding slop or generated boilerplate. If it helps you make the call, give us a star.

Star us on GitHub ★

Before you commit
get your speed potential

Run the tool. Send the report to radar@xonai.io.
We'll tell you exactly what moves — on a call.
No commitment. No infrastructure changes. No data leaves your environment.