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- [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
- ![beacon for google analytics](https://ga-beacon.appspot.com/UA-88834340-1/tantivy-cli/README)
-
-
- Tantivy-cli is the project hosting the command line interface for [tantivy](https://github.com/fulmicoton/tantivy), a search engine project.
-
-
- # Tutorial: Indexing Wikipedia with Tantivy CLI
-
- ## Introduction
-
- In this tutorial, we will create a brand new index with the articles of English wikipedia in it.
-
- ## Installing the tantivy CLI.
-
- There are simple way to add the `tantivy` CLI to your computer.
-
- If you are a rust programmer, you probably have `cargo` installed and you can just
- run `cargo install tantivy-cli`.
-
- Alternatively, if you are on `Linux 64bits`, you can directly download a
- static binary: [binaries/linux_x86_64/](http://fulmicoton.com/tantivy-files/binaries/linux_x86_64/tantivy),
- and save it in a directory of your system's `PATH`.
-
-
-
-
- ## Creating the index: `new`
-
- Let's create a directory in which your index will be stored.
-
- ```bash
- # create the directory
- mkdir wikipedia-index
- ```
-
-
- We will now initialize the index and create its schema.
- The [schema](http://fulmicoton.com/tantivy/tantivy/schema/index.html) defines
- the list of your fields, and for each field :
- - its name
- - its type, currently `u32` or `str`
- - how it should be indexed.
-
- You can find more information about the latter on
- [tantivy's schema documentation page](http://fulmicoton.com/tantivy/tantivy/schema/index.html
-
- In our case, our documents will contain
- * a title
- * a body
- * a url
-
- We want the title and the body to be tokenized and index. We want
- to also add the term frequency and term positions to our index.
- (To be honest, phrase queries are not yet implemented in tantivy,
- so the positions won't be really useful in this tutorial.)
-
- Running `tantivy new` will start a wizard that will help you go through
- the definition of the schema of our new index.
-
- Like all the other commands of `tantivy`, you will have to
- pass it your index directory via the `-i` or `--index`
- parameter as follows.
-
-
- ```bash
- tantivy new -i wikipedia-index
- ```
-
-
-
- When asked answer to the question, answer as follows:
-
- ```none
-
- Creating new index
- Let's define it's schema!
-
-
-
- New field name ? title
- Text or unsigned 32-bit Integer (T/I) ? T
- Should the field be stored (Y/N) ? Y
- Should the field be indexed (Y/N) ? Y
- Should the field be tokenized (Y/N) ? Y
- Should the term frequencies (per doc) be in the index (Y/N) ? Y
- Should the term positions (per doc) be in the index (Y/N) ? Y
- Add another field (Y/N) ? Y
-
-
-
- New field name ? body
- Text or unsigned 32-bit Integer (T/I) ? T
- Should the field be stored (Y/N) ? Y
- Should the field be indexed (Y/N) ? Y
- Should the field be tokenized (Y/N) ? Y
- Should the term frequencies (per doc) be in the index (Y/N) ? Y
- Should the term positions (per doc) be in the index (Y/N) ? Y
- Add another field (Y/N) ? Y
-
-
-
- New field name ? url
- Text or unsigned 32-bit Integer (T/I) ? T
- Should the field be stored (Y/N) ? Y
- Should the field be indexed (Y/N) ? N
- Add another field (Y/N) ? N
-
- [
- {
- "name": "title",
- "type": "text",
- "options": {
- "indexing": "position",
- "stored": true
- }
- },
- {
- "name": "body",
- "type": "text",
- "options": {
- "indexing": "position",
- "stored": true
- }
- },
- {
- "name": "url",
- "type": "text",
- "options": {
- "indexing": "unindexed",
- "stored": true
- }
- }
- ]
-
-
- ```
-
- After the wizard has finished, a `meta.json` has been written in `wikipedia-index/meta.json`.
- It is a fairly human readable JSON, so you may check its content.
-
- It contains two sections :
- - segments (currently empty, but we will change that soon)
- - schema
-
-
-
-
- # Indexing the document : `index`
-
-
- Tantivy's `index` command offers a way to index a json file.
- More accurately, the file must contain one document per line, in a json format.
- The structure of this JSON object must match that of our schema definition.
-
- ```json
- {"body": "some text", "title": "some title", "url": "http://somedomain.com"}
- ```
-
- For this tutorial, you can download a corpus with the 5 millions+ English articles of wikipedia
- formatted in the right format here : [wiki-articles.json (2.34 GB)](https://www.dropbox.com/s/wwnfnu441w1ec9p/wiki-articles.json.bz2?dl=0).
- Make sure to uncompress the file
-
- ```bash
- bunzip2 wiki-articles.json.bz2
- ```
-
- If you are in a rush you can [download 100 articles in the right format here (11 MB)](http://fulmicoton.com/tantivy-files/wiki-articles-1000.json).
-
- The `index` command will index your document.
- By default it will use as many threads as there are cores on your machine.
- You can change the number of threads by passing it the `-t` parameter.
-
- On my computer (8 core Xeon(R) CPU X3450 @ 2.67GHz), it will take around 6 minutes.
-
- ```
- cat wiki-articles.json | tantivy index -i ./wikipedia-index
- ```
-
- While it is indexing, you can peek at the index directory
- to check what is happening.
-
- ```bash
- ls ./wikipedia-index
- ```
-
- If you indexed the 5 millions articles, you should see a lot of new files, all with the following format
- The main file is `meta.json`.
-
- Our index is in fact divided in segments. Each segment acts as an individual smaller index.
- Its named is simply a uuid.
-
-
-
-
- # Serve the search index : `serve`
-
- Tantivy's cli also embeds a search server.
- You can run it with the following command.
-
- ```
- tantivy serve -i wikipedia-index
- ```
-
- By default, the server is serving on the port `3000`.
-
- You can search for the top 20 most relevant documents for the query `Barack Obama` by accessing
- the following [url](http://localhost:3000/api/?q=barack+obama&explain=true&nhits=20) in your browser
-
- http://localhost:3000/api/?q=barack+obama&explain=true&nhits=20
-
-
- # Optimizing the index : `merge`
-
- Each tantivy's indexer thread is closing a new segment every 100K documents (this is completely arbitrary at the moment).
- You should have more than 50 segments in your dictionary at the moment.
-
- Having that many queries is hurting your query performance (well, mostly the fast ones).
- Tantivy merge will merge your segment into one.
-
- ```
- tantivy merge -i ./wikipedia-index
- ```
-
- (The command takes around 7 minutes on my computer)
-
- Note that your files are still there even after having run the command.
- `meta.json` however only lists one of the segments.
- You will still need to remove the files manually.
-
-
-
-
-
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