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Home > Data > Enterprise Search > Solr Cookbook - Third Edition
Solr Cookbook - Third Edition
Solr Cookbook - Third Edition

Solr Cookbook - Third Edition: Solve real-time problems related to Apache Solr 4.x and 5.0 effectively with the help of over 100 easy-to-follow recipes , Third Edition

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Solr Cookbook - Third Edition

Chapter 2. Indexing Your Data

In this chapter, we will cover the following topics:

  • Indexing PDF files
  • Counting the number of fields
  • Using parsing update processors to parse data
  • Using scripting update processors to modify documents
  • Indexing data from a database using Data Import Handler
  • Incremental imports with DIH
  • Transforming data when using DIH
  • Indexing multiple geographical points
  • Updating document fields
  • Detecting the document language during indexation
  • Optimizing the primary key indexation
  • Handling multiple currencies

Introduction

Indexing data is one of the most crucial things in Lucene and Solr deployment. When your data is not indexed properly, your search results will be poor. When the search results are poor, it's almost certain the users will not be satisfied with the application that uses Solr. This is why we need our data to be prepared and indexed as timely and correctly as possible.

On the other hand, preparing data is not an easy task. Nowadays, we have more and more data floating around. We need to index multiple formats of data from multiple sources. Do we need to parse the data manually and prepare the data in XML format? The answer is no; we can let Solr do this for us. This chapter will concentrate on the indexing process and data preparation, starting with how to index data that is a binary PDF file to how to use Data Import Handler to fetch data from database and index it with Apache Solr and describing how we can detect the document language during indexation. We will also learn...

Indexing PDF files

The library on the corner, we used to go to, wants to expand its collection and become available for the wider public through the World Wide Web. It asked its book suppliers to provide sample chapters of all the books in PDF format so that they can share it with online users. With all the samples provided by the supplier comes a problem—how to extract data for the search box from more than 900,000 PDF files. Solr can do it with the use of Apache Tika (http://tika.apache.org/). This recipe will show you how to handle such a task.

How to do it...

To index PDF files, we will need to set up Solr to use extracting request handlers. To do this, we will take the following steps:

  1. First, let's edit our Solr instance, solrconfig.xml, and add the following configuration:
    <requestHandler name="/update/extract" class="solr.extraction.ExtractingRequestHandler">
 <lst name="defaults">
  <str name="fmap.content">text&lt...

Counting the number of fields

Imagine a situation where we have a simple document to be indexed to Solr with titles and tags. What we will want to do is separate the premium documents that have more tag values because they are better in terms of our business. Of course, we can count the number of tags ourselves, but why not let Solr do this? This recipe will show you how to do this with Solr.

How to do it...

Let's look at the steps we need to take to count the number of field values.

  1. We start with the index structure. What we need to do is put the following section in the schema.xml file:
    <field name="id" type="string" indexed="true" stored="true" required="true" />
<field name="title" type="text_general" indexed="true" stored="true"/>
<field name="tags" type="string" indexed="true" stored="true" multiValued="true"/>
<field name...

Using parsing update processors to parse data

Let's assume that we are running a bookstore, we want to sort our books by the publication date, and run faceting on the number of likes each book gets. However, we get all our data in XML, and we don't have data in the proper format, and so on. The good thing is that we can tell Solr to parse our data property so that we don't have to change what we already have. This recipe will show you how to do this.

Getting ready

Before continuing with this recipe, I suggest reading the Counting the number of fields recipe of this chapter to get used to updating the request processor configuration.

How to do it...

Let's look at the steps we need to take to make data parsing work.

  1. First, we need to prepare our index structure, so we add the following section to the schema.xml file:
    <field name="id" type="string" indexed="true" stored="true" required="true" />
<field name="title...

Using scripting update processors to modify documents

Sometimes, we need to modify documents during indexing, and we don't want to do this on the indexing application side. For example, we have documents describing the Internet sites. What we want to be able to do is filter the sites on the basis of the protocol used, for example, http or https. We don't have this information; we only have the whole URL address. Let's see how we can achieve this with Solr.

Getting ready

Before continuing with the following recipe, I suggest reading the Counting the number of fields recipe of this chapter to get used to updating request processor configuration.

How to do it...

The following steps will take you through the process of achieving our goal:

  1. First, we start with the index structure, putting the following section in the schema.xml file:
    <field name="id" type="string" indexed="true" stored="true" required="true" />
<field name=...

Indexing data from a database using Data Import Handler

One of our clients has a problem. His database of users grows to such a size that even a simple SQL select takes too much time, and he seeks how to improve the search times. Of course, he has heard about Solr, but he doesn't want to generate XML or any other data format and push it to Solr; he would like the data to be fetched. What can we do about it? Well, there is one thing—we can use one of the contribute modules of Solr, which is the Data Import Handler. This task will show you how to configure the basic setup of the Data Import Handler and how to use it.

How to do it...

Let's assume that we have a database table. To select users from our table, we use the following SQL query:

SELECT user_id, user_name FROM users

The response might look like this:

| user_id | user_name     |
| 1       | John Kowalski |
| 2       | Amanda Looks  |

We also have a second table called users_description, where we store the descriptions of...

Introduction

Indexing data is one of the most crucial things in Lucene and Solr deployment. When your data is not indexed properly, your search results will be poor. When the search results are poor, it's almost certain the users will not be satisfied with the application that uses Solr. This is why we need our data to be prepared and indexed as timely and correctly as possible.

On the other hand, preparing data is not an easy task. Nowadays, we have more and more data floating around. We need to index multiple formats of data from multiple sources. Do we need to parse the data manually and prepare the data in XML format? The answer is no; we can let Solr do this for us. This chapter will concentrate on the indexing process and data preparation, starting with how to index data that is a binary PDF file to how to use Data Import Handler to fetch data from database and index it with Apache Solr and describing how we can detect the document language during indexation. We will also learn how...

Indexing PDF files

The library on the corner, we used to go to, wants to expand its collection and become available for the wider public through the World Wide Web. It asked its book suppliers to provide sample chapters of all the books in PDF format so that they can share it with online users. With all the samples provided by the supplier comes a problem—how to extract data for the search box from more than 900,000 PDF files. Solr can do it with the use of Apache Tika (http://tika.apache.org/). This recipe will show you how to handle such a task.

How to do it...

To index PDF files, we will need to set up Solr to use extracting request handlers. To do this, we will take the following steps:

  1. First, let's edit our Solr instance, solrconfig.xml, and add the following configuration:

    <requestHandler name="/update/extract" class="solr.extraction.ExtractingRequestHandler">
 <lst name="defaults">
  <str name="fmap.content">text</str>
  <str name="lowernames">true</str...

Counting the number of fields

Imagine a situation where we have a simple document to be indexed to Solr with titles and tags. What we will want to do is separate the premium documents that have more tag values because they are better in terms of our business. Of course, we can count the number of tags ourselves, but why not let Solr do this? This recipe will show you how to do this with Solr.

How to do it...

Let's look at the steps we need to take to count the number of field values.

  1. We start with the index structure. What we need to do is put the following section in the schema.xml file:

    <field name="id" type="string" indexed="true" stored="true" required="true" />
<field name="title" type="text_general" indexed="true" stored="true"/>
<field name="tags" type="string" indexed="true" stored="true" multiValued="true"/>
<field name="tags_count" type="int" indexed="true" stored="true"/>

  2. The next thing is our test data, which looks as follows:

    <add>
 <doc>
  &lt...

Using parsing update processors to parse data

Let's assume that we are running a bookstore, we want to sort our books by the publication date, and run faceting on the number of likes each book gets. However, we get all our data in XML, and we don't have data in the proper format, and so on. The good thing is that we can tell Solr to parse our data property so that we don't have to change what we already have. This recipe will show you how to do this.

Getting ready

Before continuing with this recipe, I suggest reading the Counting the number of fields recipe of this chapter to get used to updating the request processor configuration.

How to do it...

Let's look at the steps we need to take to make data parsing work.

  1. First, we need to prepare our index structure, so we add the following section to the schema.xml file:

    <field name="id" type="string" indexed="true" stored="true" required="true" />
<field name="title" type="text_general" indexed="true" stored="true" />
<field name="published...

Using scripting update processors to modify documents

Sometimes, we need to modify documents during indexing, and we don't want to do this on the indexing application side. For example, we have documents describing the Internet sites. What we want to be able to do is filter the sites on the basis of the protocol used, for example, http or https. We don't have this information; we only have the whole URL address. Let's see how we can achieve this with Solr.

Getting ready

Before continuing with the following recipe, I suggest reading the Counting the number of fields recipe of this chapter to get used to updating request processor configuration.

How to do it...

The following steps will take you through the process of achieving our goal:

  1. First, we start with the index structure, putting the following section in the schema.xml file:

    <field name="id" type="string" indexed="true" stored="true" required="true" />
<field name="url" type="text_general" indexed="true" stored="true"/>
<field...

Indexing data from a database using Data Import Handler

One of our clients has a problem. His database of users grows to such a size that even a simple SQL select takes too much time, and he seeks how to improve the search times. Of course, he has heard about Solr, but he doesn't want to generate XML or any other data format and push it to Solr; he would like the data to be fetched. What can we do about it? Well, there is one thing—we can use one of the contribute modules of Solr, which is the Data Import Handler. This task will show you how to configure the basic setup of the Data Import Handler and how to use it.

How to do it...

Let's assume that we have a database table. To select users from our table, we use the following SQL query:

SELECT user_id, user_name FROM users

The response might look like this:

| user_id | user_name     |
| 1       | John Kowalski |
| 2       | Amanda Looks  |

We also have a second table called users_description, where we store the descriptions of users. The SQL query...

Incremental imports with DIH

In most use cases, indexing the data from scratch during every indexation doesn't make sense. Why index your 1,00,000 documents when only 1,000 were modified or added? This is where the Solr Data Import Handler delta queries come in handy. Using them, we can index our data incrementally. This recipe will show you how to set up the Data Import Handler to use delta queries and index data in an incremental way.

Getting ready

Refer to the Indexing data from a database using Data Import Handler recipe in this chapter to get to know the basics of the Data Import Handler configuration. I assume that Solr is set up according to the description given in the mentioned recipe.

How to do it...

We will reuse parts of the configuration shown in the Indexing data from a database using Data Import Handler recipe in this chapter, and we will modify it. Execute the following steps:

  1. The first thing you should do is add an additional column to the tables you use, a column that will specify...

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Description

This book is for intermediate Solr Developers who are willing to learn and implement Pro-level practices, techniques, and solutions. This edition will specifically appeal to developers who wish to quickly get to grips with the changes and new features of Apache Solr 5.

What you will learn

  • Acquire the skills needed to index your data in different formats, forms, and sources
  • Overcome common problems while analyzing your data
  • Use the faceting mechanism to get aggregated information about your data
  • Improve your Solr instance and Solr cluster performance
  • Get to know how to configure and use SolrCloud
  • Make use of the highlighting and document grouping functionalities
  • Diagnose and resolve problems with Solr instances and clusters
  • Implement different autocomplete functionalities

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 23, 2015
Length: 356 pages
Edition : 3rd
Language : English
ISBN-13 : 9781783553150
Vendor :
Apache
Category :
Data
Languages :
Java
Concepts :
Enterprise Search
Tools :
Solr

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Product Details

Publication date : Jan 23, 2015
Length: 356 pages
Edition : 3rd
Language : English
ISBN-13 : 9781783553150
Vendor :
Apache
Category :
Data
Languages :
Java
Concepts :
Enterprise Search
Tools :
Solr

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Table of Contents

11 Chapters
1. Apache Solr Configuration Chevron down icon Chevron up icon
1. Apache Solr Configuration
Introduction
Running Solr on a standalone Jetty
Installing ZooKeeper for SolrCloud
Migrating configuration from master-slave to SolrCloud
Choosing the proper directory configuration
Configuring the Solr spellchecker
Using Solr in a schemaless mode
Limiting I/O usage
Using core discovery
Configuring SolrCloud for NRT use cases
Configuring SolrCloud for high-indexing use cases
Configuring SolrCloud for high-querying use cases
Configuring the Solr heartbeat mechanism
Changing similarity
2. Indexing Your Data Chevron down icon Chevron up icon
2. Indexing Your Data
Introduction
Indexing PDF files
Counting the number of fields
Using parsing update processors to parse data
Using scripting update processors to modify documents
Indexing data from a database using Data Import Handler
Incremental imports with DIH
Transforming data when using DIH
Indexing multiple geographical points
Updating document fields
Detecting the document language during indexation
Optimizing the primary key indexation
Handling multiple currencies
3. Analyzing Your Text Data Chevron down icon Chevron up icon
3. Analyzing Your Text Data
Introduction
Using the enumeration type
Removing HTML tags during indexing
Storing data outside of Solr index
Using synonyms
Stemming different languages
Using nonaggressive stemmers
Using the n-gram approach to do performant trailing wildcard searches
Using position increment to divide sentences
Using patterns to replace tokens
4. Querying Solr Chevron down icon Chevron up icon
4. Querying Solr
Introduction
Understanding and using the Lucene query language
Using position aware queries
Using boosting with autocomplete
Phrase queries with shingles
Handling user queries without errors
Handling hierarchies with nested documents
Sorting data on the basis of a function value
Controlling the number of terms needed to match
Affecting document score using function queries
Using simple nested queries
Using the Solr document query join functionality
Handling typos with n-grams
Rescoring query results
5. Faceting Chevron down icon Chevron up icon
5. Faceting
Introduction
Getting the number of documents with the same field value
Getting the number of documents with the same value range
Getting the number of documents matching the query and subquery
Removing filters from faceting results
Using decision tree faceting
Calculating faceting for relevant documents in groups
Improving faceting performance for low cardinality fields
6. Improving Solr Performance Chevron down icon Chevron up icon
6. Improving Solr Performance
Introduction
Handling deep paging efficiently
Configuring the document cache
Configuring the query result cache
Configuring the filter cache
Improving Solr query performance after the start and commit operations
Lowering the memory consumption of faceting and sorting
Speeding up indexing with Solr segment merge tuning
Avoiding caching of rare filters to improve the performance
Controlling the filter execution to improve expensive filter performance
Configuring numerical fields for high-performance sorting and range queries
7. In the Cloud Chevron down icon Chevron up icon
7. In the Cloud
Introduction
Creating a new SolrCloud cluster
Setting up multiple collections on a single cluster
Splitting shards
Having more than a single shard from a collection on a node
Creating a collection on defined nodes
Adding replicas after collection creation
Removing replicas
Moving shards between nodes
Using aliasing
Using routing
8. Using Additional Functionalities Chevron down icon Chevron up icon
8. Using Additional Functionalities
Introduction
Finding similar documents
Highlighting fragments found in documents
Efficient highlighting
Using versioning
Retrieving information about the index structure
Altering the index structure on a live collection
Grouping documents by the field value
Grouping documents by the query value
Grouping documents by the function value
Efficient documents grouping using the post filter
9. Dealing with Problems Chevron down icon Chevron up icon
9. Dealing with Problems
Introduction
Dealing with the too many opened files exception
Diagnosing and dealing with memory problems
Configuring sorting for non-English languages
Migrating data to another collection
SolrCloud read-side fault tolerance
Using the check index functionality
Adjusting the Jetty configuration to avoid deadlocks
Tuning segment merging
Avoiding swapping
10. Real-life Situations Chevron down icon Chevron up icon
10. Real-life Situations
Introduction
Implementing the autocomplete functionality for products
Implementing the autocomplete functionality for categories
Handling time-sliced data using aliases
Boosting words closer to each other
Using the Solr spellchecking functionality
Using the Solr administration panel for monitoring
Automatically expiring Solr documents
Exporting whole query results
Index Chevron down icon Chevron up icon
Index

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Markus Klose Mar 11, 2015
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This question is answered by Rafal Kuc in the current version of his Apache Solr cookbook.In "Solr Cookbook Third Edition" he describes typical problems, use cases and their solutions.The book is written for developers who already have background knowledge on Apache Solr.The structure of the book and its chapters provides a fast and efficient way of reading. You can either read the book from the beginning to the end or select a specific chapter without encountering any trouble. There are only a few dependencies between a few chapters. If there are any, the author explicitly points them out.The book is divided into ten chapters and covers important topics such as "Solr configuration", "performance optimization" or "SolrCloud".Each of these chapters describe several issues and how to deal with them. The structure of such an issue is uniform throughout the book and makes it easy getting along. The initial description of the problem or the scenario is followed by the step by step solution with Apache Solr. The author does not stop here, but continues with a detailed and sophisticated description of the background.In the description of the problem the author uses simple sample data and describes the solution based on it. This allows quite a simple recreation of the problem and also an understanding of the solution.The problems and solutions collected in this book range from simple configurations to more complex scenarios that are encountered again and again when building web applications with Apache Solr. The recently released version of Solr 5.0 is taken into account within the third edition of this book.Many of the described use cases are found in one form or another already answered in forums or mailing lists. But for me, and I consider myself an experienced Apache Solr user, there was a lot to discover. I saw some new and interesting approaches in this book, which I will try in my next projects.The book is a fine collection of everyday problems and saves you the hassle of searching for a solution in the world wide web.Conclusion: This book is not an introduction to the Apache Solr and therefore it is not suitable for beginners. However it is a great reference book, which offers practical solutions to everyday problems with Apache Solr.I recommend this book to everyone who deals with Apache Solr to read this book as a supplement to the relevant documentation of Apache Solr.
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Recendo Jun 18, 2015
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Eine stark lösungs-orientierte und angenehme Systematik zieht sich durch das ganze Buch: (1) Aufgabe - (2) Umgesetzte Lösung als Code-Fragment - (3) Erklärung der Lösung. Wer im Inhalt(s-Verzeichnis) das findet, was er sucht, wird gut bedient.Die Lösungen beziehen sich auf die 4er- Solr Versionen. Die derzeit aktuelle Version Solr 5 ist, nach Aussage des Autors, immerhin als Beta-Version für Kompatibilitäts-Tests berücksichtigt worden, auf zusätzliche Version-5 Features geht er jedoch nicht ein.Der Inhalt des Buchs wendet sich hauptsächlich an Admins oder Dev-Ops, weniger an Data-Scientists. Bspw. wird das Thema Solr-Cloud gut abgedeckt, das Thema Daten-Clustering hingegen wird nicht berührt.Rein inhaltlich bewertend, möchte ich dem Buch 'vier bis fünf' Sterne geben.Jedoch! Der vollständige Copy-Schutz des Buchs behindert ein leichtes und fehlerfreies Arbeiten mit der elektronischen Version dieses Buchs. Ständig war ich versucht, die (teilweise über zwei Seiten gehenden) Code-Fragmente zu kopieren, und direkt in die eigene Solr-Konfiguration zu übertragen. Geht nicht. Punkt. Und da auch der separate Download des Codes (von der Verlags-Site), nicht "1 zu 1" der Buch-Vorlage entspricht, wird ein schnelles und fehlerbefreites Arbeiten erfolgreich behindert.Hätte ja Verständnis, wenn allein der begleitende Buch-Text geschützt wäre. Das kann aber kaum für Code-Fragmente in einem IT-Arbeits-Buch gelten ... dass einem, als ein bezahlender Leser, derartige Erschwernisse in den Weg gelegt werden, ist schlicht grotesk. So er sich nicht zu nicht-legalen Methoden der DRM-Entfernung oder Umwegen verführen lassen möchte -> wird der Leser faktisch gezwungen, eine Technik des 19. Jahrhunderts ( das manuelle Abschreiben ) - in einer Arbeitsumgebung des 21 Jahrhunderts ( Copy & Paste ) - zu verwenden. IMHO, das macht nicht-glücklich, überhaupt nicht!Eigentlich sollte man durch die Vergabe nur eines einzelnen Bewertung-Sterns ein deutlicheres Zeichen gegen diese (meines Erachtens) käufer-missachtende Form der Durchsetzung des Kopierschutzes setzen. Allerdings, es war meine Entscheidung, die Kindle-Version zu kaufen. Und damit zugleich auch modernere Erwartungen und Maßstäbe, als an ein Produkt des 16. Jahrhunderts, zu stellen. Deswegen, der Fairness und Achtung gegenüber Werk und Autor wegen, und auch der Hoffnung halber, dass andere Rezendenten ebenfalls deutliche Worte gegenüber derart problematischen Formen der Durchsetzung des DRM einbringen werden, ziehe ich der gekauften Kindle-Version, lediglich 0,5 Sterne ab.
Amazon Verified review Amazon
NOTiFY Apr 06, 2016
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Bought it prior to going on the Sematext Core Solr – 2 Day Workshop in London (April 2016) which the author Rafal Kuc is the trainer.I like the "Cookbook" format as it allows you to go directly to the problem/issue you're attempting to solve/implement. The book got me started with Solr and had my database imported, indexed and was searching it within a few hours. Found it very to useful to have (skim) read it prior to course.I recommend the book and the attending the Sematext Core Solr workshop.
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Dale Brooks Aug 02, 2015
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very pleased with the additional details and practical experience points that I found in this book, above and beyond the standard Apache documentation
Amazon Verified review Amazon
DJ Apr 26, 2015
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I am a big fan of the "cookbook" format, and have several "cookbooks" on other technologies, that I refer to often. The format is a little different then the other cookbooks I am used to, instead of a the "problem", "solution", "discussion", and "see also" format; this has a longer "scenario" which isn't as clear and concise as an ORA cookbook, a "getting ready" which often sends you out to read other material, then a "how to do it", "How it works", and then a "see also". The problems/scenarios are not as clear as other cookbooks.As with most cookbooks this is not really a book you would read cover to cover but flip through as you encounter issues. But since I planned to review the book, I started from the beginning, and was turned off initially. The problems seemed to be more one off niche types of problems, I almost stopped reading. However, as I flipped deeper into the book and found better content that was more relevant to what I need using Solr. In some places the content seemed to be kind of forced into a cookbook format, such as a "recipe" called "Understanding and using the Lucene query language"So while there was some good content in the book, don't let the beginning of the book deter you, it did not match the expectations I would have for a "cookbook". Make sure you read the table of contents before purchasing, and if you can look at some of the recipes in the later portion of the book. There are definitely some good examples that could save you some time, and some examples to get you familiar with patterns in using Solr.Disclosure: I was provided a free version of the book for review.
Amazon Verified review Amazon

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About the author

Profile icon Rafal Kuc
Rafal Kuc
Rafał Kuć is a software engineer, trainer, speaker and consultant. He is working as a consultant and software engineer at Sematext Group Inc. where he concentrates on open source technologies such as Apache Lucene, Solr, and Elasticsearch. He has more than 14 years of experience in various software domains—from banking software to e–commerce products. He is mainly focused on Java; however, he is open to every tool and programming language that might help him to achieve his goals easily and quickly. Rafał is also one of the founders of the solr.pl site, where he tries to share his knowledge and help people solve their Solr and Lucene problems. He is also a speaker at various conferences around the world such as Lucene Eurocon, Berlin Buzzwords, ApacheCon, Lucene/Solr Revolution, Velocity, and DevOps Days. Rafał began his journey with Lucene in 2002; however, it wasn't love at first sight. When he came back to Lucene in late 2003, he revised his thoughts about the framework and saw the potential in search technologies. Then Solr came and that was it. He started working with Elasticsearch in the middle of 2010. At present, Lucene, Solr, Elasticsearch, and information retrieval are his main areas of interest. Rafał is also the author of the Solr Cookbook series, ElasticSearch Server and its second edition, and the first and second editions of Mastering ElasticSearch, all published by Packt Publishing.
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