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elastic
elasticsearch
Java2010–2024
elastic / elasticsearch

elasticsearch

Free and Open Source, Distributed, RESTful Search Engine

Systems & InfrastructureSearch & Information Retrieval
Explore on GitHubRead Hacker News discussions
74Distinct people
88Mentions
0Explicit recommenders
78.7KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Free and Open Source, Distributed, RESTful Search Engine

GitHub

Where it is used

  • GitHub — GitHub uses Elasticsearch to power its search services as the core search engine. Source
  • anyone — “Anyone.com, a global AI-powered real estate platform, replaced a Postgres search back end it had outgrown with Elasticsearch, moving 210 million production records onto a single index in about a week and a half and consolidating its entire search infrastructure into three lines of Terraform.” Source
  • 1 more documented example

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

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 5:58:02 AM 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 year88 dated mentions

Observed mentions: 2010-07-20 20:38:02 UTC to 2024-10-29 14:01:46 UTC.

0510152010-01-01 00:00:00 UTC to 2011-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20102011-01-01 00:00:00 UTC to 2012-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2012-01-01 00:00:00 UTC to 2013-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 8 mentions; 1 submissions, 7 comments2014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 8 mentions; 2 submissions, 6 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 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): 15 mentions; 1 submissions, 14 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 10 mentions; 0 submissions, 10 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 14 mentions; 0 submissions, 14 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 7 mentions; 0 submissions, 7 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2024

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
20102010-01-01 00:00:00 UTC2011-01-01 00:00:00 UTC101
20112011-01-01 00:00:00 UTC2012-01-01 00:00:00 UTC000
20122012-01-01 00:00:00 UTC2013-01-01 00:00:00 UTC101
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC817
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC808
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC826
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC413
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC202
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 UTC15114
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC10010
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC14014
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC808
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC707
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC110

What Hacker News says

8 sources
yehosef·Oct 12, 2015
Clinton explains in https://github.com/elastic/elasticsearch/issues/9112 why they don't support this. If you really need it, you can implement it yourself by limiting the aggregation using filters https://www.elastic.co/guide/en/elasticsearch/reference/curr... it's obviously not real pagination but the github issue explains why it isn't practical. If you know of other systems that have paginations of aggregations, perhaps you can reference those sources in the github issues and they can learn some tricks how to do it. As for top hits, the "from" option doesn't let you do what you want?
In Elasticsearch 2.0.0-rc1 released
eclark·May 5, 2015
Jepsen is just doing a kill -9 on the java process. I posted a comment on the blog: https://aphyr.com/posts/323-call-me-maybe-elasticsearch-1-5-... First I made sure that read() goes through the page cache. (It does as long as there's no O_DIRECT) Then I went and checked the write ahead log on ES. Turns out from my reading that ES is considering a write to be durable if it is put into a userspace buffer. https://github.com/elastic/elasticsearch/blob/master/src/mai... Data is pushed to kernel space whenever the buffer gets full. Then it is fsync'd on the timer.
In Call me maybe: Elasticsearch 1.5.0
dobe·Apr 7, 2015
I guess you are talking about the plan to have the data of one shard only on one disk (see https://github.com/elastic/elasticsearch/issues/9498)? This does not necessarily mean that you will end up having only one shard per datapath - only if you have just one shard per node. But you are right, the change might lead to unbalanced disk usage in some scenarios, where increasing the number of shards would solve the problem. There are two options: 1. (Recommended for now) Export the table with COPY TO ( https://crate.io/docs/stable/sql/reference/copy_to.html). Drop the table and then import it again using COPY FROM (https://crate.io/docs/stable/sql/reference/copy_from.html ). 2. Use insert by query (see https://crate.io/docs/stable/sql/dml.html#inserting-data-by-... ) if it is ok for you to copy the whole data to another table (with more shar
Read the rest
ds). 1) is recommended, since it allows for throttling on import time (see https://crate.io/docs/en/latest/best_practice/data_import.ht...) and also does not require a rename of a table, which is currently not implemented but is on our backlog. However i think once ES 2.0 is out we will have table renames and also throttling in insert by query, so option 2) will be recommended then. Our genreal recommendation to the fixed number of shards limitation is to choose a higher number of shards upfront (number of expected cores matches the most use cases) or to use partitioned tables (https://crate.io/docs/en/latest/sql/partitioned_tables.html) where possible since those allow to change the number of shards for future partitions.
In Crate: Distributed SQL Database for the Age of Docker

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