architecture and implementation of apache lucene pdf

Architecture And Implementation Of Apache Lucene Pdf

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Apache Lucene is a free and open-source search engine software library , originally written completely in Java by Doug Cutting. Doug Cutting originally wrote Lucene in It joined the Apache Software Foundation's Jakarta family of open-source Java products in September and became its own top-level Apache project in February The name Lucene is Doug Cutting's wife's middle name and her maternal grandmother's first name. Lucene formerly included a number of sub-projects, such as Lucene.

Solr Tutorial

This tutorial covers getting Solr up and running, ingesting a variety of data sources into Solr collections, and getting a feel for the Solr administrative and search interfaces. The tutorial is organized into three sections that each build on the one before it. The first exercise will ask you to start Solr, create a collection, index some basic documents, and then perform some searches. The second exercise works with a different set of data, and explores requesting facets with the dataset.

The third exercise encourages you to begin to work with your own data and start a plan for your implementation. For best results, please run the browser showing this tutorial and the Solr server on the same machine so tutorial links will correctly point to your Solr server.

Begin by unzipping the Solr release and changing your working directory to the subdirectory where Solr was installed. This exercise will walk you through how to start Solr as a two-node cluster both nodes on the same machine and create a collection during startup.

Then you will index some sample data that ships with Solr and do some basic searches. This will start an interactive session that will start two Solr "servers" on your machine. The first prompt asks how many nodes we want to run. Note the [2] at the end of the last line; that is the default number of nodes.

Two is what we want for this example, so you can simply press enter. This will be the port that the first node runs on. Unless you know you have something else running on port on your machine, accept this default option also by pressing enter. If something is already using that port, you will be asked to choose another port. This is the port the second node will run on.

Again, unless you know you have something else running on port on your machine, accept this default option also by pressing enter. Solr will now initialize itself and start running on those two nodes. The script will print the commands it uses for your reference.

Notice that two instances of Solr have started on two nodes. Because we are starting in SolrCloud mode, and did not define any details about an external ZooKeeper cluster, Solr launches its own ZooKeeper and connects both nodes to it. This tutorial will ask you to index some sample data included with Solr, called the "techproducts" data.

Enter techproducts at the prompt and hit enter. This is asking how many shards you want to split your index into across the two nodes. Choosing "2" the default means we will split the index relatively evenly across both nodes, which is a good way to start. Accept the default by hitting enter. Again, the default of "2" is fine to start with here also, so accept the default by hitting enter. Solr has two sample sets of configuration files called a configset available out-of-the-box.

A collection must have a configset, which at a minimum includes the two main configuration files for Solr: the schema file named either managed-schema or schema. The question here is which configset you would like to start with. At this point, Solr will create the collection and again output to the screen the commands it issues. This is the main starting point for administering Solr. Solr will now be running two "nodes", one on port and one on port There is one collection created automatically, techproducts , a two shard collection, each with two replicas.

The Cloud tab in the Admin UI diagrams the collection nicely:. If you click on it, your browser will show you the raw response. All of the documents are not returned to us, however, because of the default for a parameter called rows , which you can see in the form is You can change the parameter in the UI or in the defaults if you wish. But we can cover some of the most common types of queries. The response indicates that there are 4 hits "numFound" Note the responseHeader before the documents.

This header will include the parameters you have set for the search. By default it shows only the parameters you have set for this query, which in this case is only your query term.

The documents we got back include all the fields for each document that were indexed. This is, again, default behavior. If you want to restrict the fields in the response, you can use the fl parameter, which takes a comma-separated list of field names.

This is one of the available fields on the query form in the Admin UI. Put "id" without quotes in the "fl" box and hit Execute Query again. Or, to specify it with curl:. All Solr queries look for documents using some field. This is possible with the use of copy fields, which are set up already with this set of configurations.

Sometimes, though, you want to limit your query to a single field. This can make your queries more efficient and the results more relevant for users. Much of the data in our small sample data set is related to products. In the Query screen, enter "electronics" without quotes in the q box and hit Execute Query. You should get 14 results, such as:. This search finds all documents that contain the term "electronics" anywhere in the indexed fields.

However, we can see from the above there is a cat field for "category". If we limit our search for only documents with the category "electronics", the results will be more precise for our users. Now you get 12 results:.

Documents containing more terms will be sorted higher in the results list. We have only scratched the surface of the search options available in Solr. For more Solr search options, see the section on Searching. You can choose now to continue to the next example which will introduce more Solr concepts, such as faceting results and managing your schema, or you can strike out on your own. This starts the first node. It also automatically creates new fields in the schema for new fields that appear in incoming documents.

This mode is called "Schemaless". When you initially started Solr in the first exercise, we had a choice of a configset to use. The one we chose had a schema that was pre-defined for the data we later indexed. Whoa, wait. We did, however, set two parameters -s and -rf. Those are the number of shards to split the collection across 2 and how many replicas to create 2. This is equivalent to the options we had during the interactive example from the first exercise. The first thing the command printed was a warning about not using this configset in production.

Otherwise, though, the collection should be created. Second, we are using "field guessing", which is configured in the solrconfig. Field guessing is designed to allow us to start using Solr without having to define all the fields we think will be in our documents before trying to index them. This is why we call it "schemaless", because you can start quickly and let Solr create fields for you as it encounters them in documents. Sounds great! Well, not really, there are limitations. For these reasons, the Solr community does not recommend going to production without a schema that you have defined yourself.

By this we mean that the schemaless features are fine to start with, but you should still always make sure your schema matches your expectations for how you want your data indexed and how users are going to query it.

It is possible to mix schemaless features with a defined schema. Using the Schema API, you can define a few fields that you know you want to control, and let Solr guess others that are less important or which you are confident through testing will be guessed to your satisfaction.

The films data we are going to index has a small number of fields for each movie: an ID, director name s , film name, release date, and genre s. As the first document in the dataset, Solr is going to guess the field type based on the data in the record. If we go ahead and index this data, that first film name is going to indicate to Solr that that field type is a "float" numeric field, and will create a "name" field with a type FloatPointField.

All data after this record will be expected to be a float. We have titles like A Mighty Wind and Chicken Run , which are strings - decidedly not numeric and not floats. If we let Solr guess the "name" field is a float, what will happen is later titles will cause an error and indexing will fail. What we can do is set up the "name" field in Solr before we index the data to be sure Solr always interprets it as a string.

At the command line, enter this curl command:. It will not be permitted to have multiple values, but it will be stored meaning it can be retrieved by queries. You can also use the Admin UI to create fields, but it offers a bit less control over the properties of your field. It will work for our case, though:. We would need to define a field to search for every query. In the Admin UI, choose Add Copy Field , then fill out the source and destination for your field, as in this screenshot.

You could simply supply the directory where this file resides, but since you know the format you want to index, specifying the exact file for that format is more efficient.

Apache Lucene: free search for your website

Nowadays, if you think of a search engine, Google will probably pop into your head first. Website operators also use Google in the form of a Custom Search Engine CSE to offer users a quick and easy search function for their own content. There are, of course, other possibilities to offer your visitors a full-featured text search that might work better for you. You can use Lucene instead: a free open source project from Apache. Numerous companies have integrated Apache Lucene — either online or offline.

This tutorial covers getting Solr up and running, ingesting a variety of data sources into Solr collections, and getting a feel for the Solr administrative and search interfaces. The tutorial is organized into three sections that each build on the one before it. The first exercise will ask you to start Solr, create a collection, index some basic documents, and then perform some searches. The second exercise works with a different set of data, and explores requesting facets with the dataset. The third exercise encourages you to begin to work with your own data and start a plan for your implementation. For best results, please run the browser showing this tutorial and the Solr server on the same machine so tutorial links will correctly point to your Solr server. Begin by unzipping the Solr release and changing your working directory to the subdirectory where Solr was installed.

This document defines the index file formats used in Lucene version 3. Apache Lucene is written in Java, but several efforts are underway to write versions of Lucene in other programming languages. If these versions are to remain compatible with Apache Lucene, then a language-independent definition of the Lucene index format is required. This document thus attempts to provide a complete and independent definition of the Apache Lucene 3. As Lucene evolves, this document should evolve. Versions of Lucene in different programming languages should endeavor to agree on file formats, and generate new versions of this document.


Architecture and Implementation of Apache Lucene page 1 Theimplementation steps of a document handler for Pdf files using the Lucene documenthandler.


Apache Lucene

Easily build search and index capabilities into your applications. Lucene is an open source, highly scalable text search-engine library available from the Apache Software Foundation. You can use Lucene in commercial and open source applications. Lucene's powerful APIs focus mainly on text indexing and searching. It can be used to build search capabilities for applications such as e-mail clients, mailing lists, Web searches, database search, etc.

Please do not add your website if it uses Lucene merely indirectly, e. We reserve the right to remove links where it isn't visible that Lucene is used, so consider adding a text like "powered by Lucene" to your search result page. Note to spammers: don't bother adding your site here, we're using the appropriate meta tags so search engines will ignore the links anyway. Also note, if you don't at least provide some hint at how you use Lucene i.

This document is intended as a "getting started" guide. It has three audiences: first-time users looking to install Apache Lucene in their application or web server; developers looking to modify or base the applications they develop on Lucene; and developers looking to become involved in and contribute to the development of Lucene. This document is written in tutorial and walk-through format.

Using Apache Lucene to search text

Architecture and Implementation of Apache Lucene

Embed Size px x x x x DeclarationThis Thesis is the result of my own independent work, except where otherwise stated. Othersources are acknowledge explicit reference. This work has not been previously accepted in substance for any degree and is not beingcurrently submitted in candidature for any degree. Gieen, November Josiane, Gamgo i 3. AbstractThe purpose of this thesis was to study the architecture and implementation of ApacheLucene.

If you want to supply your own ContentHandler for Solr to use, you can extend the ExtractingRequestHandler and override the createFactory method. This factory is responsible for constructing the SolrContentHandler that interacts with Tika, and allows literals to override Tika-parsed values. Set the parameter literalsOverride , which normally defaults to true , to false to append Tika-parsed values to literal values.

Apache Lucene - Getting Started Guide

Building applications using Lucene

Он смотрел на девушку, понимая, что его поиски подошли к концу. Она вымыла голову и переоделась - быть может, считая, что так легче будет продать кольцо, - но в Нью-Йорк не улетела. Беккер с трудом сдерживал волнение. Его безумная поездка вот-вот закончится. Он посмотрел на ее пальцы, но не увидел никакого кольца и перевел взгляд на сумку. Вот где кольцо! - подумал.  - В сумке.

Танкадо неоднократно публично заявлял, что у него есть партнер. Наверное, этим он надеялся помешать производителям программного обеспечения организовать нападение на него и выкрасть пароль. Он пригрозил, что в случае нечестной игры его партнер обнародует пароль, и тогда все эти фирмы сойдутся в схватке за то, что перестало быть секретом. - Умно, - сказала Сьюзан. Стратмор продолжал: - Несколько раз Танкадо публично называл имя своего партнера.

Мысли Стратмора судорожно метались в поисках решения. Всегда есть какой-то выход. Наконец он заговорил - спокойно, тихо и даже печально: - Нет, Грег, извини. Я не могу тебя отпустить. Хейл даже замер от неожиданности.

Apache Lucene - Index File Formats

 - Какой смысл хлестать мертвую кобылу. Парень был уже мертв, когда прибыла скорая. Они пощупали пульс и увезли его, оставив меня один на один с этим идиотом-полицейским.

Японские иероглифы не спутаешь с латиницей. Он сказал, что выгравированные буквы выглядят так, будто кошка прошлась по клавишам пишущей машинки. - Коммандер, не думаете же вы… - Сьюзан расхохоталась. Но Стратмор не дал ей договорить. - Сьюзан, это же абсолютно ясно.

Фильтры служили куда более высокой цели - защите главной базы данных АНБ. Чатрукьяну была известна история ее создания. Несмотря на все предпринятые в конце 1970-х годов усилия министерства обороны сохранить Интернет для себя, этот инструмент оказался настолько соблазнительным, что не мог не привлечь к себе внимания всего общества. Со временем им заинтересовались университеты, а вскоре после этого появились и коммерческие серверы. Шлюзы открылись - в Интернет хлынула публика.

Но все доказательства к этому моменту будут уничтожены, и Стратмор сможет сказать, что не знает, о чем речь. Бесконечная работа компьютера. Невзламываемый шифр.

Она кружила по пустому кабинету, все еще не преодолев ужас, который вызвало у нее общение с Хейлом. Надо выбираться из шифровалки. Черт с ней, с Цифровой крепостью. Пришла пора действовать. Нужно выключить ТРАНСТЕКСТ и бежать.

Наконец-то, подумал пассажир такси. Наконец-то. ГЛАВА 77 Стратмор остановился на площадке у своего кабинета, держа перед собой пистолет. Сьюзан шла следом за ним, размышляя, по-прежнему ли Хейл прячется в Третьем узле.

 - Во множестве шифров применяются группы из четырех знаков. Возможно, это и есть ключ. - Вот именно, - простонал Джабба.  - Он над вами издевается.

Apache Lucene
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