spark-advisor-rules
Deterministic rules engine for Apache Spark job analysis. Part of the spark-advisor ecosystem.
Install
pip install spark-advisor-rules
What it detects
17 rules that identify common Spark performance problems:
| Rule | Detects |
|---|---|
| DataSkewRule | Task duration skew (max/median > 5x) |
| SpillToDiskRule | Disk spill indicating insufficient memory |
| GCPressureRule | GC time > 20% of task time |
| ShufflePartitionsRule | Partition count far from optimal (128MB target) |
| ExecutorIdleRule | Slot utilization < 40% (CRITICAL if <20%) |
| TaskFailureRule | Failed tasks (CRITICAL if >=10, WARNING if >0) |
| SmallFileRule | Avg input bytes per task < 10MB (CRITICAL if <1MB) |
| BroadcastJoinThresholdRule | Broadcast join disabled or too low |
| SerializerChoiceRule | Java serializer used with shuffle stages |
| DynamicAllocationRule | Missing min/max bounds or disabled |
| ExecutorMemoryOverheadRule | High GC + high memory utilization |
All thresholds are configurable via Thresholds model.
Usage
from spark_advisor_rules.static_analysis import StaticAnalysisService
service = StaticAnalysisService()
results = service.analyze(job_analysis)
Links
License
Apache 2.0
1 maintainer
Metadata
1 maintainer
Release files for spark-advisor-rules 0.1.21
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| spark_advisor_rules-0.1.21.tar.gz | 13.1 kB | Without provenance | Details for spark_advisor_rules-0.1.21.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| spark_advisor_rules-0.1.21-py3-none-any.whl | Python 3 | none | any | Details for spark_advisor_rules-0.1.21-py3-none-any.whl |
Total release size: 23.5 kB
Release files / spark_advisor_rules-0.1.21.tar.gz
| Download URL | spark_advisor_rules-0.1.21.tar.gz |
|---|---|
| Size | 13.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
774506c15f96a2a853c76f91f0dc2b89761275bccdb411728d081a3f120a6b8d
|
|
BLAKE2b-256 checksum How to use checksums |
1f581d8b4dd605a09989c907b995886d5090dd7f4c46c37ee4fdc410add34037
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.11.2 {"installer":{"name":"uv","version":"0.11.2","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Release files / spark_advisor_rules-0.1.21-py3-none-any.whl
| Download URL | spark_advisor_rules-0.1.21-py3-none-any.whl |
|---|---|
| Size | 10.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a7d86984b8dccd952df3e3868324582ee3d31f693c49c1759063ce5643a7f2c3
|
|
BLAKE2b-256 checksum How to use checksums |
9a5854d7dea70e825ad2d29f40a5845fd8bd15e2578a1e9944add3354bf0f0ca
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.11.2 {"installer":{"name":"uv","version":"0.11.2","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Security for spark-advisor-rules 0.1.21
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
