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apache
lucene-solr
Data & Databases2015–2020
apache / lucene-solr

lucene-solr

Apache Lucene and Solr open-source search software

8Distinct people
8Mentions
0Explicit recommenders
4.4KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Apache Lucene and Solr open-source search software

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year8 dated mentions

Observed mentions: 2015-02-18 23:41:44 UTC to 2020-10-06 05:40:28 UTC.

012342015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20152016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2020

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC101
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC413
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC202

What Hacker News says

8 sources
Just off the top of my head, there are .NET copies of: - Akka https://github.com/akka/akka - Lucene https://github.com/apache/lucene-solr - Aeron https://github.com/real-logic/aeron - Retrofit https://github.com/square/retrofit Not to mention projects like Apache Spark, Cassandra, Elasticsearch, Druid - Java projects. Many projects (Foundation DB, Scylla DB, I could find more) will have in-house support for Java and not .NET. The .NET equivalents to these libraries tend to be playing catch up. Xamarin Android will always be playing catch-up to Android's Java/Kotlin APIs for Android. Big machine learning projects like PyTorch and TensorFlow tend to give first-class support of some fashion to a Java API (mostly due to Android). Is there a .NET equivalent to Deeplearning4j? Hadoop? Hive? Kakfa? In Java there is a proliferation of web project
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s: Spring, Vert.x, Quarkus, Micronaut, Play 2, Spark Java; Netty, Jetty, Apache. In .NET all you ever hear about is Microsoft projects ASP.NET core; Kestrel, IIS. Working as a .NET dev, when there is an SDK, if it's not from Microsoft, it's clear the .NET SDK is a lower priority for bug fixes and new features compared to e.g. the Java/Python/etc.
In .NET Orleans
That's because that page explains how to turn the mode on and off, how to fine-tune it (e.g. different date formats) and how to index formats other than JSON. Elasticsearch does not support a good chunk of this, so no need to document. If you want a more streamlined version, you can check the example instead: https://github.com/apache/lucene-solr/blob/master/solr/examp... And even then, it will already discuss the problem with auto-guessing the content types, something that Elasticsearch mentions only later. Solr is just more upfront and explicit about the issues. Still, you do have a point, Solr documentation tries to be comprehensive rather than ease-of-use oriented. That sometimes obscures the easy things.
In AWS Elasticsearch: a fundamentally-flawed offering
This is the commit containing the code that Elastic says was copied by Search Guard: https://github.com/floragunncom/search-guard-enterprise-modu... In particular, the change to getLiveDocs(): https://github.com/floragunncom/search-guard-enterprise-modu... and numDocs(): https://github.com/floragunncom/search-guard-enterprise-modu... EDIT: At least in the case of numDocs(), both Elastic and Search Guard's implementations seem to be based on this bit of Apache-licensed code from Lucene (or perhaps this is just a common pattern for counting live documents?): https://github.com/apache/lucene-solr/blob/branch_6_3/lucene...
In Dear Search Guard Users
Yea, webpack sure is horrible. Not like C/C++ programs, where we have a super simple setup of Make, config, and autoconf. Like checkout this easy-peasy Make file: https://github.com/apache/httpd/blob/trunk/Makefile.in . Even a child could understand it. Or look at Java. Who has ever seen a complicated ant or pom file? No one ever. This Lucene ant file practically wrote itself: https://github.com/apache/lucene-solr/blob/master/lucene/bui... /s I guess my snarky point is that build systems are complicated. It's like the Bjarne Stroustrup about programming languages. There are two kinds of build systems: the ones people complain about the ones no body uses. Robust build systems have to handle the nearly endless combinations of different requirements each app brings to the table...complexity is table stakes. Modern web apps are built to be ab
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le to run on a myriad of different platforms, as they have to maintain compatibility between tons of version of several different browsers running on a slew of different device types running different operating systems. Did we think that was going to be easy? People like to shit on webpack, but I don't get it. It's a well thought out tool that works extremely well. And what are the alternatives? Yes, yes, yes, I know, your blog/website/thing you have is just plain ol' html and and you stick some javascript in a script tag or whatever. No need for any of these fancy build scripts, blah, blah. So what? That's like telling the people at lucene that all this arcane index stuff is overkill because you just search your hard drive using ripgrep. You can't make a real app like Slack, Spotify, VS Code, or Google Docs without a serious build process. People are making photoshop, for the browser. They're not going to do it with ES3 they write directly into a script tag.
In Stepping Away from Sass
I went through the list and the comment about Apache Lucene really piqued my interest. I found the Lucene code in GitHub but some of the sources have more boilerplate Java comments than code! Anyways, I remembered Java Docs are often excellent so here's the Lucene Java Docs: https://lucene.apache.org/core/7_5_0/core/index.html From my experience, studying the API Docs for Java and using it as a guide to the code makes understanding the code much easier. The code is here: https://github.com/apache/lucene-solr
In Programs to Read
Lucene has had this capability for a while now. A regexp query (as defined by the RegExp class) is compiled into an automaton for quick comparison with the inverted index, also represented as an automaton. Automatons and FSTs are used extensively by Lucene these days. Out of curiosity, I did some playing around with Lucene's RegExp class when it first came out (or rather, when I first learned about it). It provides a really interesting way to build regular expressions: https://gist.github.com/mumrah/6104234 Javadoc: https://lucene.apache.org/core/4_0_0/core/org/apache/lucene/... Source: https://github.com/apache/lucene-solr/blob/trunk/lucene/core...
In RE2/J: Linear time regular expression matching in Java

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