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This is for #173 Not sure how to handle all the exposition removed from the README. Maybe I should leave it? It doesn't really fit that neatly into examples because a lot of the coode is just introducing data types and linking off to ES docs.
173 lines
6.2 KiB
Markdown
173 lines
6.2 KiB
Markdown
Bloodhound [](https://travis-ci.org/bitemyapp/bloodhound) [](https://hackage.haskell.org/package/bloodhound)
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==========
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Elasticsearch client and query DSL for Haskell
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==============================================
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Why?
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----
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Search doesn't have to be hard. Let the dog do it.
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Endorsements
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------------
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"Bloodhound makes Elasticsearch almost tolerable!" - Almost-gruntled user
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"ES is a nightmare but Bloodhound at least makes it tolerable." - Same user, later opinion.
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Version compatibility
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---------------------
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As of version 0.13.0.0, Bloodhound has 2 separate module trees for
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ElasticSearch versions 1 and 5. Import the module that is appropriate
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for your use case. If you would like to add support for another major
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version, open a ticket expressing your intend and follow the pattern
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used for other versions. We weighed the idea of sharing code between
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versions but it just got too messy, especially considering the
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instability of the ElasticSearch API. We switched to a model which
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would allow the persons responsible for a particular protocol version
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to maintain that version while avoiding conflict with other versions.
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See our [TravisCI](https://travis-ci.org/bitemyapp/bloodhound) for a
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listing of ElasticSearch version we test against.
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Stability
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---------
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Bloodhound is stable for production use. I will strive to avoid breaking API compatibility from here on forward, but dramatic features like a type-safe, fully integrated mapping API may require breaking things in the future.
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Testing
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---------
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The TravisCI tests are run using [Stack](http://docs.haskellstack.org/en/stable/README.html). You should use Stack instead of `cabal` to build and test Bloodhound to avoid compatibility problems. You will also need to have an ElasticSearch instance running at `localhost:9200` in order to execute some of the tests. See the "Version compatibility" section above for a list of ElasticSearch versions that are officially validated against in TravisCI.
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Steps to run the tests locally:
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1. Dig through the [past releases] (https://www.elastic.co/downloads/past-releases) section of the ElasticSearch download page and install the desired ElasticSearch versions.
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2. Install [Stack] (http://docs.haskellstack.org/en/stable/README.html#how-to-install)
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3. In your local Bloodhound directory, run `stack setup && stack build`
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4. Start the desired version of ElasticSearch at `localhost:9200`, which should be the default.
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5. Run `stack test` in your local Bloodhound directory.
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6. The unit tests will pass if you re-execute `stack test`. If you want to start with a clean slate, stop your ElasticSearch instance, delete the `data/` folder in the ElasticSearch installation, restart ElasticSearch, and re-run `stack test`.
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Hackage page and Haddock documentation
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======================================
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<http://hackage.haskell.org/package/bloodhound>
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Elasticsearch Tutorial
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======================
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It's not using Bloodhound, but if you need an introduction to or overview of Elasticsearch and how to use it, you can use [this screencast](https://vimeo.com/106463167).
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Examples
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========
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See the [examples](htts://github.com/bitemyapp/bloodhound/tree/master/examples) directory for example code.
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Contributors
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============
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* [Chris Allen](https://github.com/bitemyapp)
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* [Liam Atkinson](https://github.com/latkins)
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* [Christopher Guiney](https://github.com/chrisguiney)
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* [Curtis Carter](https://github.com/ccarter)
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* [Michael Xavier](https://github.com/MichaelXavier)
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* [Bob Long](https://github.com/bobjflong)
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* [Maximilian Tagher](https://github.com/MaxGabriel)
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* [Anna Kopp](https://github.com/annakopp)
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* [Matvey B. Aksenov](https://github.com/supki)
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* [Jan-Philip Loos](https://github.com/MaxDaten)
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Possible future functionality
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=============================
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Span Queries
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------------
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Beginning here: <https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-first-query.html>
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Function Score Query
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--------------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html>
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Node discovery and failover
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---------------------------
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Might require TCP support.
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Support for TCP access to Elasticsearch
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---------------------------------------
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Pretend to be a transport client?
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Bulk cluster-join merge
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-----------------------
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Might require making a lucene index on disk with the appropriate format.
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GeoShapeQuery
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-------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-geo-shape-query.html>
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GeoShapeFilter
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--------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-geo-shape-filter.html>
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Geohash cell filter
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-------------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-geohash-cell-filter.html>
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HasChild Filter
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---------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-has-child-filter.html>
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HasParent Filter
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----------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-has-parent-filter.html>
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Indices Filter
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--------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-indices-filter.html>
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Query Filter
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------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-query-filter.html>
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Script based sorting
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--------------------
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-sort.html#_script_based_sorting>
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Collapsing redundantly nested and/or structures
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-----------------------------------------------
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The Seminearring instance, if deeply nested can possibly produce nested structure that is redundant. Depending on how this affects ES performance, reducing this structure might be valuable.
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Runtime checking for cycles in data structures
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----------------------------------------------
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check for n \> 1 occurrences in DFS:
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<http://hackage.haskell.org/package/stable-maps-0.0.5/docs/System-Mem-StableName-Dynamic.html>
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<http://hackage.haskell.org/package/stable-maps-0.0.5/docs/System-Mem-StableName-Dynamic-Map.html>
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Photo Origin
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============
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Photo from HA! Designs: <https://www.flickr.com/photos/hadesigns/>
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