Apache Solr
duckdf
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Apache Solr | duckdf | |
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31 | 3 | |
4,365 | 41 | |
0.0% | - | |
0.0 | 0.0 | |
2 months ago | 4 months ago | |
Java | R | |
Apache License 2.0 | GNU General Public License v3.0 only |
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Apache Solr
- Iniciando no Elasticsearch: Conceitos básicos
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YaCy, a distributed Web Search Engine, based on a peer-to-peer network
There are already many project about search:
- https://www.marginalia.nu/
- https://searchmysite.net/
- https://lucene.apache.org/
- elastic search
- https://presearch.com/
- https://stract.com/
- https://wiby.me/
I think that all project are fun. I would like to see one succeeding at reaching mainstream level of attention.
I have also been gathering links meta data for some time. Maybe I will use them to feed any eventual self hosted search engine, or language model, if I decide to experiment with that.
- domains for seed https://github.com/rumca-js/Internet-Places-Database
- bookmarks seed https://github.com/rumca-js/RSS-Link-Database
- links for year https://github.com/rumca-js/RSS-Link-Database-2024
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Getting started with Elasticsearch + Python
Elasticsearch is based on Lucene and is used by various companies and developers across the world to build custom search solutions.
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Tools to use to query and index data?
elastic search is kinda heavyweight infra for a small project. Its built on top of apache lucene (https://lucene.apache.org), which you can use directly.
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Top metrics for Elasticsearch monitoring with Prometheus
Elasticsearch is based on Lucene, which is built in Java. This means that monitoring the Java Virtual Machine (JVM) memory is crucial to understand the current usage of the whole system.
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Cross data type search that wasn’t supported well using Elasticsearch
Apache Lucene which seems to have a lot more features than Elasticsearch
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How to find closest keyphrase match in text?
Generally with term vectors and a tf-idf index. Lucene is a good starting place to help.
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Java Library to perform string search
try elasticsearch or solr, behind the scenes they both use https://lucene.apache.org/ if you don't want basically a full nosql database service, but I'd just slap solr up and call it a day.
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Top 8 Open-Source Observability & Testing Tools
OpenSearch is an open-source database to ingest, search, visualize, and analyze data. It’s built on top of Apache Lucerce, a FOSS library for indexing and search, which OpenSearch leverages for more advanced analytics capabilities, like anomaly detection, machine learning, full-text search, and more.
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grep like search with preprocessing
Lucene is the thing you think you need. Elastic Search is a nice wrapper for it. But these are Java, so maybe you want Sphinx Search (C++) or MeiliSearch (Rust).
duckdf
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DuckDB – in-process SQL OLAP database management system
Quite a while ago, when duckdb was just a duckling, I wrote an R package that supported direct manipulation of R dataframes using SQL.[1] duckdb was the engine for this.
The approach was never as fast as data.table but did approach the speed of dplyr for more complex queries.
Life had other things in store for me and I haven’t touched this library for a while now.
At the time there was no Julia connector for duckdb, but now that there is, I’d like to try this approach in that language.
[1] https://github.com/phillc73/duckdf
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ClickHouse as an alternative to Elasticsearch for log storage and analysis
Yeah, I agree sqldf is quite slow. Fair point.
As you've seen, duckdb registers an "R data frame as a virtual table." I'm not sure what they mean by "yet" either.
Of course it is possible to write an R dataframe to an on-disk duckdb table, if that's what you want to do.
There are some simple benchmarks on the bottom of the duckdf README[1]. Essentially I found for basic SQL SELECT queries, dplyr is quicker, but for much more complex queries, the duckdf/duckdb combination performs better.
If you really want speed of course, just use data.table.
[1] https://github.com/phillc73/duckdf
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Julia 1.6: what has changed since Julia 1.0?
That's a really good point that I'd not really thought about. I'd never really considered the difference between calling just functions versus macros.
Thinking about Query.jl and DataFramesMeta.jl, and I am for sure not an expert in either, I can't specifically speak to your `head` example, but other base functions can be combined with macros. For example, see the LINQ examples from DataFramesMeta.jl[1] where `mean` is being used. Or again the LINQ style examples in Query.jl[2], where `descending` is used in the first example, or `length` later in the Grouping examples.
Is that the kind of thing you meant?
For whatever reason, with the way my brain is wired, the LINQ style of query just works for me. I have never directly used LINQ, but do have some SQL experience. In fact, I wrote some dinky little wrapper functions[3] around duckdb[4] so I could directly query R dataframes and datatables with SQL using that backend, rather than sqldf[5].
[1] https://juliadata.github.io/DataFramesMeta.jl/stable/#@linq-...
[2] https://www.queryverse.org/Query.jl/stable/linqquerycommands...
[3] https://github.com/phillc73/duckdf
[4] https://duckdb.org/
[5] https://cran.r-project.org/web/packages/sqldf/index.html
What are some alternatives?
OpenSearch - 🔎 Open source distributed and RESTful search engine.
tidyquery - Query R data frames with SQL
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
julia - The Julia Programming Language
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
loki - Like Prometheus, but for logs.
Makie.jl - Interactive data visualizations and plotting in Julia
Apache Lucene - Apache Lucene.NET