https://github.com/capillariesio/capillaries
Distributed batch data processing framework
https://github.com/capillariesio/capillaries
batch-processing cassandra dag distributed-computing distributed-systems go golang rabbitmq relational-algebra workflow-engine workflows
Last synced: 2 months ago
JSON representation
Distributed batch data processing framework
- Host: GitHub
- URL: https://github.com/capillariesio/capillaries
- Owner: capillariesio
- License: mit
- Created: 2022-09-24T19:11:20.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-08-09T17:14:47.000Z (about 1 year ago)
- Last Synced: 2024-08-09T18:54:07.028Z (about 1 year ago)
- Topics: batch-processing, cassandra, dag, distributed-computing, distributed-systems, go, golang, rabbitmq, relational-algebra, workflow-engine, workflows
- Language: Go
- Homepage:
- Size: 5.35 MB
- Stars: 59
- Watchers: 0
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-go - capillaries - distributed batch data processing framework. (Distributed Systems / Search and Analytic Databases)
- awesome-go - capillariesio/capillaries
- awesome-go - capillariesio/capillaries
README
[](https://coveralls.io/github/capillariesio/capillaries?branch=main) [](https://goreportcard.com/report/github.com/capillariesio/capillaries) [](https://pkg.go.dev/github.com/capillariesio/capillaries)
Capillaries is a data processing framework that:
- addresses scalability issues and manages intermediate data storage, enabling users to focus on data transforms and quality control;
- bridges the gap between distributed, scalable data processing/integration solutions and the necessity to produce enriched, customer-ready, production-quality, human-curated data within SLA time limits.
This is a GitHub readme. More details and a blog at https://capillaries.io.
## Why Capillaries?
| | BEFORE | AFTER |
| ----------- | ------ |------ |
| Cloud-friendly | Depends | Can be deployed to the cloud within minutes; Docker-ready |
| Data aggregation | SQL joins | Capillaries [lookups](doc/glossary.md#lookup) in Cassandra + [Go expressions](doc/glossary.md#go-expressions) (scalability, parallel execution) |
| Data filtering | SQL queries, custom code | [Go expressions](doc/glossary.md#go-expressions) (scalability, maintainability) |
| Data transform | SQL expressions, custom code | [Go expressions](doc/glossary.md#go-expressions), Python [formulas](doc/glossary.md#py_calc-processor) (parallel execution, maintainability) |
| Intermediate data storage | Files, relational databases | on-the-fly-created Cassandra [keyspaces](doc/glossary.md#keyspace) and [tables](doc/glossary.md#table) (scalability, maintainability) |
| Workflow execution | Shell scripts, custom code, workflow frameworks | RabbitMQ as scheduler, workflow status stored in Cassandra (parallel execution, fault tolerance, incremental computing) |
| Workflow monitoring and interaction | Custom solutions | Capillaries [UI](ui/README.md), [Toolbelt](doc/glossary.md#toolbelt) utility, [API](doc/api.md), [Web API](doc/glossary.md#webapi) (transparency, operator validation support) |
| Workflow management | Shell scripts, custom code | Capillaries configuration: [script file](doc/glossary.md#script) with [DAG](doc/glossary.md#dag), Python [formulas](doc/glossary.md#py_calc-processor) |
## Getting started
On Mac, WSL or Linux, run in bash shell:
```
git clone https://github.com/capillariesio/capillaries.git
cd capillaries
./copy_demo_data.sh
docker compose -p "test_capillaries_containers" up
```
Navigate to `http://localhost:8080` to see [Capillaries UI](./doc/glossary.md#capillaries-ui), wait until it shows the `Keyspaces` screen with no errors. It may take a while - all docker containers must start and Cassandra must be fully initialized. Now Capillaries is ready to process sample demo input data according to the sample demo scripts (all copied by copy_demo_data.sh above).
Start a new Capillaries [data processing run](./doc/glossary.md#run) by clicking "New run" and providing the following parameters (no tabs or spaces allowed in textboxes):
| Field | Value |
|- | - |
| Keyspace | portfolio_quicktest |
| Script URI | /tmp/capi_cfg/portfolio_quicktest/script_quick.json |
| Script parameters URI | /tmp/capi_cfg/portfolio_quicktest/script_params_quick_fs_one.json |
| Start nodes | 1_read_accounts,1_read_txns,1_read_period_holdings |
Alternatively, you can start a new [run](./doc/glossary.md#run) using Capillaries [toolbelt](./doc/glossary.md#toolbelt) by executing the following command from the Docker host machine, it should have the same effect as starting a run from the UI:
```
docker exec -it capillaries_webapi /usr/local/bin/capitoolbelt start_run -script_file=/tmp/capi_cfg/portfolio_quicktest/script_quick.json -params_file=/tmp/capi_cfg/portfolio_quicktest/script_params_quick_fs_one.json -keyspace=portfolio_quicktest -start_nodes=1_read_accounts,1_read_txns,1_read_period_holdings
```
Watch the progress in Capillaries UI. A new keyspace `portfolio_quicktest` will appear in the keyspace list. Click on it and watch the run complete - nodes `7_file_account_period_sector_perf` and `7_file_account_year_perf` should produce result files:
```
cat /tmp/capi_out/portfolio_quicktest/account_period_sector_perf.csv
cat /tmp/capi_out/portfolio_quicktest/account_year_perf.csv
```
## Monitoring your test runs
Besides [Capillaries UI](./doc/glossary.md#capillaries-ui) at `http://localhost:8080`, you may want to check out the stats provided by other tools.
Log messages generated by:
- Capillaries [Daemon](./doc/glossary.md#daemon)
- Capillaries [WebAPI](./doc/glossary.md#webapi)
- Capillaries [UI](./doc/glossary.md#capillaries-ui)
- RabbitMQ
- Cassandra with Prometheus jmx-exporter
- Prometheus
are collected by fluentd and saved in /tmp/capi_log.
To see Cassandra cluster status, run this command (reset JVM_OPTS so jmx-exporter doesn't try to attach to the nodetool JMV process):
```
docker exec -e JVM_OPTS= capillaries_cassandra1 nodetool status
```
Cassandra read/write statistics and some Daemon/Webapi metrics collected by Prometheus available at:
`http://localhost:9090/query?g0.expr=sum%28irate%28cassandra_clientrequest_localrequests_count%7Bclientrequest%3D%22Write%22%7D%5B1m%5D%29%29&g0.show_tree=0&g0.tab=graph&g0.range_input=15m&g0.res_type=auto&g0.res_density=medium&g0.display_mode=lines&g0.show_exemplars=1&g1.expr=sum%28irate%28cassandra_clientrequest_localrequests_count%7Bclientrequest%3D%22Read%22%7D%5B1m%5D%29%29&g1.show_tree=0&g1.tab=graph&g1.range_input=15m&g1.res_type=auto&g1.res_density=medium&g1.display_mode=lines&g1.show_exemplars=0&g2.expr=irate%28capi_script_def_cache_hit_count%5B1m%5D%29&g2.show_tree=0&g2.tab=graph&g2.range_input=15m&g2.res_type=auto&g2.res_density=medium&g2.display_mode=lines&g2.show_exemplars=0&g3.expr=irate%28capi_script_def_cache_miss_count%5B1m%5D%29&g3.show_tree=0&g3.tab=graph&g3.range_input=15m&g3.res_type=auto&g3.res_density=medium&g3.display_mode=lines&g3.show_exemplars=0`
## Further steps
### Blog at capillaries.io
For more details about this particular demo, see Capillaries blog: [Use Capillaries to calculate ARK portfolio performance](https://capillaries.io/blog/2023-04-08-portfolio/index.html). To learn how this demo runs on a bigger dataset with 14 million transactions, see [Capillaries: ARK portfolio performance calculation at scale](https://capillaries.io/blog/2023-11-15-portfolio-scale/index.html).
### Further introduction
For more details about getting started, see [Getting started](doc/started.md).
### Deploy Capillaries at scale
#### Container-based deployments
Capillaries binaries are intended to be container-friendly. Check out the `docker-compose.yml` and [Kubernetes deployment POC](./deploy/k8s/README.md), these test projects may be a good starting point for creating your full-scale container-based deployment.
#### VM-based deployment
See [Terraform script](./deploy/tf/cassandra_cluster/README.md) that creates Capillaries deployment in AWS.
## Capillaries in depth
### [What it is and what it is not](doc/what.md) (use case discussion and diagrams)
### [Getting started](doc/started.md) (run a quick Docker-based demo without compiling a single line of code)
### [Testing](doc/testing.md)
### [Toolbelt, Daemon, and Webapi configuration](doc/binconfig.md)
### [Script configuration](doc/scriptconfig.md)
### [Capillaries UI](ui/README.md)
### [Capillaries API](doc/api.md)
### [Glossary](doc/glossary.md)
### [Q & A](doc/qna.md)
### [Capillaries blog](https://capillaries.io/blog/index.html)
### [MIT License](LICENSE)
(C) 2022-2025 KH (kleines.hertz[at]protonmail.com)
