H2 VS elasticsearch-mapper-attachments

The URL should point to a particular comment, but HN removes fragments: https://github.com/h2database/h2database/issues/3686#issueco...

This sounds very much like the idiocy of "infosec" lunkheads who know nothing about what they're "fixing" but if an automated system tells them a CVE exists, they've absolutely got to have it "patched". They don't look into what the claims of the CVE are, or whether their specific use case is vulnerable. They don't know, they don't care, they're not even programmers. All they know is a box needs ticking.

A similar thing happened with h2database - a "security researcher" found that if you do something you're told not to do, then bad things happen.. but they demanded and got a CVE allocated anyway. Anyone who looks at it realises it's bullshit, but the mere existence of a CVE is all that matters to these idiots.

What the h2database developer said about it: https://github.com/h2database/h2database/issues/3686#issueco...

> I struggle to understand why I should feel the slightest shred of sympathy for "major corporations" that are using a volunteer-developed open-source project. Feel free to get your corporation to pay someone to deal with this, or pay for a similar commercial library.

> ...than it would be to learn the exact syntax and quirks and possibly bugs of someone else's implementation...

Yup. Also, having deep knowledge of the language is required.

SQLite's grammar is neat. Creating a compatible parser would make a fun project. Here's a pretty good example: https://github.com/bkiers/sqlite-parser (Actual ANTLR 4 grammar: https://github.com/bkiers/sqlite-parser/blob/master/src/main... )

Postgres, which tries to be compliant with the latest standards, however...

SQL-2016 is a beast. Not to mention all the dialects.

I'm updating my personal (soon to be FOSS) grammar from ANTLR 3 LL(k) to ANTLR 4 ALL().

I've long had a working knowledge of SQL-92, with some SQL-1999 (eg common table expressions).

But the new structures and extensions are a bit overwhelming.

Fortunately, ANTLR project has ~dozen FOSS grammars to learn from. https://github.com/antlr/grammars-v4/tree/master/sql

They mostly mechanically translate BNFs to LL(k) with some ALL(). Meaning few take advantage of left-recursion. https://github.com/antlr/antlr4/blob/master/doc/left-recursi...

Honestly, I struggled to understand these grammars. Plus, not being conversant with the SQL-2016 was a huge impediment. Just finding a succinct corbis of test cases was a huge hurdle for me.

Fortunately, the H2 Database project is a great resource. https://github.com/h2database/h2database/tree/master/h2/src/...

Now for the exciting conclusion...

My ANTLR grammar which passes all of H2's tests looks nothing like any of the official or product specific BNFs.

Further, I found discrepancy between the product specific BNFs and their implementations.

So a lot of trial & error is required for a "real world" parser. Which would explain why the professional SQL parsing tools charge money.

I still think creating a parser for SQLite is a great project.

H2 - Free, Embedded & Open source

H2 2.1

H2 for mocking relational database connections

It's open-source and written in Java, so you can even create custom procedures and register them straight in your application!

Firstly, let's set up a basic Spring Boot application. We can use the Spring Initializr with Spring Data JPA, H2 Database, Lombok added. H2 Database will provide us with a simple database, and Spring Data JPA will allow us to easily interact with it using Hibernate. Lombok will make it easier to write concise and readable classes.

Sorting chunks by similarity: commonly used tools don't do that. Most archive tools only sort by file type.

I wrote a tool that chunks the data (into variable-sized blocks, to re-sync if there are multiple files that have different length prefixes, but that's another story), and then sorts the chunks by LSH (locality sensitive hash). LSH is used by search engines to detect similar text. It can compress directories that contain multiple version of e.g. source code very well (e.g. trunk, branches). https://github.com/h2database/h2database/blob/master/h2/src/...

I discussed this approach with a researcher in this area in January 2020. AFAIK there is active research in this area, specially to compress DNA sequences. But he also wasn't aware of papers or research in this area for general-purpose data compression.

So, I think this area is largely uncharted. I would be interested (as a hobby side project) to help, if somebody is interested.

Elasticsearch - www.elastic.co/

The increasing complexity of modern systems led to the rise of AIOps (Artificial Intelligence for IT Operations) and observability practices. AIOps leveraged machine learning algorithms to automate problem detection, analysis, and resolution. Observability focused on gaining insights into system behaviour through metrics, logs, and traces. As a result, tools like Prometheus, Grafana, and ELK stack (Elasticsearch, Logstash, Kibana) gained popularity.

My only experience with NetFlow collection is on my home firewall/router running pfSense Community Edition, which is free to download and can be installed on a wide assortment of X86 hardware. I installed the Softflowd package, which exports NetFlow data to a dedicated Elasticsearch/Logstash/Kibana (ELK) server on my LAN. I believe Security Onion and ElastiFlow also can be NetFlow collectors.

Elasticsearch, Logstash, and Kibana (ELK) Stack: An open source suite of tools for log management and analysis, providing real-time insights into security events.

Recently I have taken an interest in big data. https://neo4j.com/ , https://cassandra.apache.org/ , https://clickhouse.com/, https://www.elastic.co/ - are all databases I have experience with. Neo4j and Cassandra only as a hobby, but Clickhouse I have used in production, and Elasticsearch I have used for some 7 years now.

Buy an enterprise-class, wired router like the Negate 2100 ($349 USD), which runs pfSense, and configure the Deco AXE5400 device(s) to operate in Access Point Mode. Then install the Softflowd package through the pfSense web UI. Softflowd will collect and export NetFlow data to a NefFlow collector, which is the separate computer/VM/container referred to above, running software like Security Onion, ElastiFlow, or Elasticsearch/Logstash/Kibana (ELK).

If you’re unaware, elastic search is some like enterprise level search shit. They just put it in a theme. https://www.elastic.co

systemctl status kibana ● kibana.service - Kibana Loaded: loaded (/etc/systemd/system/kibana.service; enabled; vendor preset: enabled) Active: active (running) since Tue 2023-03-28 09:40:05 UTC; 33min ago Docs: https://www.elastic.co Main PID: 3168 (node) Tasks: 11 (limit: 9432) Memory: 303.3M CPU: 35.190s CGroup: /system.slice/kibana.service └─3168 /usr/share/kibana/bin/../node/bin/node /usr/share/kibana/bin/../src/cli/dist --logging.dest=/var/log/kibana/kibana.log --pid.file=/run/kibana/kibana.pid "--deprecation.skip_deprecated_settings[0]=logging.dest" Mar 28 09:40:05 wazuh systemd[1]: Started Kibana.