asami
pyroscope
Our great sponsors
asami | pyroscope | |
---|---|---|
6 | 56 | |
626 | 7,382 | |
0.6% | - | |
0.0 | 9.6 | |
about 2 years ago | about 1 year ago | |
Clojure | Go | |
Eclipse Public License 1.0 | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
asami
- Ask HN: What are some 'cool' but obscure data structures you know about?
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Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
Unlike some other commenters, I agree that graph models are usually a better fit for most data than relational models. There's been some interesting work in recent years developing this idea: in the Clojure world there's Datomic, XTDB, and a host of competitors, all of which build on work from Semantic Web/SPARQL/triplestores and logic programming. Some are even intended to be used as primary datastores: they support some amount of schema and constraints, have well-defined consistency and ACID guarantees, etc. This makes them unlike graph databases like Neo4J and others, which fill an architectural role more like Elasticsearch as a read-optimization tool. Here's an interesting talk making a case for triple-based databases.
- Introduction to the Asami Graph Database
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How to query Datomic, Datascript, Asami, or other graph databases
Despite the documentation that exists, I've heard many people who have been confused about how to query Datomic, Datascript, Asami, or other graph databases. So I've made an attempt at explaining it https://github.com/threatgrid/asami/wiki/Introduction
- Introduction (To Graph Databases)
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Asami
The first Graph implementation for Asami was a simple in-memory data structure, described in my ClojureD talk. The code for this appears in asami.index. This file started much smaller (as referenced above), but has since expanded with the needs extended functionality, such as transactions, and transitive closure operations.
pyroscope
- Grafana Phlare, open source database for continuous profiling at scale
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The pros and cons of eBPF profiling in K8s
What do you mean? pyroscope.io was slow for you? or the blog?
- Go garbage collector doesn't release memory
- Pyroscope - Continuous profiling platform
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Ask HN: What are some 'cool' but obscure data structures you know about?
Tries (or prefix trees).
We use them a lot at Pyroscope for compressing strings that have common prefixes. They are also used in databases (e.g indexes in Mongo) or file formats (e.g debug symbols in macOS/iOS Mach-O format are compressed using tries).
We have an article with some animations that go into details about tries in case anyone's interested [0].
[0] https://github.com/pyroscope-io/pyroscope/blob/main/docs/sto...
- How to add dynamic tags/labels to Java profiles (example)
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Question: How do you handle oversized heap analysis?
You could use continuous profiling with Pyroscope which uses async-profiler under the hood, but with the added functionality that you can add relevant tags to your VMs (example).
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JFR (Java Flight Recorder) Parser written in Go
Java Flight Recorder (JFR) is a format for collecting diagnostic and profiling data from Java applications. A while back someone created an issue for Pyroscope , an open source continuous profiler written in Go, to support ingesting profiles in JFR format, but there were no existing parsers that were also written in Go.
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flamegraph.com - a new website for uploading, analyzing, and sharing pprof profiles
This cloud version is actually a slimmed-down version of Pyroscope which is open source and so you can run it locally.
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We created flamegraph.com - A website for uploading, analyzing, and sharing flamegraphs
At Pyroscope (open source continuous profiling) we use flamegraphs extensively to visualize and analyze profiling data. However, one of the worst parts about using flamegraphs for analysis is that they are kind of annoying to share.
What are some alternatives?
datascript - Immutable database and Datalog query engine for Clojure, ClojureScript and JS
parca - Continuous profiling for analysis of CPU and memory usage, down to the line number and throughout time. Saving infrastructure cost, improving performance, and increasing reliability.
crux - General purpose bitemporal database for SQL, Datalog & graph queries. Backed by @juxt [Moved to: https://github.com/xtdb/xtdb]
profefe - Continuous profiling for long-term postmortem analysis
datahike - A durable Datalog implementation adaptable for distribution.
barrier - Open-source KVM software
datalevin - A simple, fast and versatile Datalog database
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Apache AGE - Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL. [Moved to: https://github.com/apache/age]
SheetJS js-xlsx - 📗 SheetJS Spreadsheet Data Toolkit -- New home https://git.sheetjs.com/SheetJS/sheetjs
naga - Datalog based rules engine
Oat++ - 🌱Light and powerful C++ web framework for highly scalable and resource-efficient web application. It's zero-dependency and easy-portable.