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最全面solrr入门教程

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搜索引擎技术系列教材（一）- solr - Solr 入门教程

步骤 1 : 关于JDK版本

至少使用JDK8版本，请下载JDK8或者更高版本：下载以及配置JDK环境

步骤 2 : 什么是 Solr

前面学习了Lucene, 现在开始学习Solr。
以连接数据库为类比：Lucene 就相当于JDBC，是基本的用法。
Solr 就相当 Mybatis，方便开发人员配置，访问和调用。
而且Solr 被做成了 webapp形式，以tomcat的应用的方式启动，提供了可视化的配置界面

步骤 3 : 下载 Solr

下载区(点击进入)下载 solr-7.2.1.rar 并解压。
截至目前 (2018-3-10) 使用的最新版本是7.2.1

步骤 4 : 启动服务器

我的解压目录在 D:\software\solr-7.2.1

cd D:\software\solr-7.2.1\bin

solr.cmd start

如此就启动了服务器，会占用端口8983。倘若端口被占用，会启动失败，排查办法请看端口被占用

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步骤 5 : 访问服务器

输入地址：

http://127.0.0.1:8983/solr/#/

就可以访问Solr 服务器了

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步骤 6 : 继续

但是这仅仅是个开始，为了能够使用Solr服务器还需要跟多的工作，请继续往下学习

搜索引擎技术系列教材（二）- solr - 创建Core

步骤 1 : Core 概念

如果说Solr相当于一个数据库的话，那么Core就相当于一张表

步骤 2 : 不要通过图形界面创建Core

如图所示，通过图形界面创建Core会失败，应该使用命令行方式创建Core

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步骤 3 : 命令行方式创建Core

如图所示就创建了 Core

cd D:\software\solr-7.2.1\bin

solr.cmd create -c how2java

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步骤 4 : 删除 new_core

如果点击了步骤不要通过图形界面创建Core 里的图形界面里的 Add Core,那么就会一直有错误提醒，那么按照如下方式删除 new_core 就不会再有错误提醒了

cd D:\software\solr-7.2.1\bin

solr.cmd delete -c new_core

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搜索引擎技术系列教材（三）- solr - Solr7.2 可以用的中文分词器 IKAnalyzer6.5.0.jar

步骤 1 : 没有中文分词

默认情况下是没有中文分词的，如图所示，通过点击左边的how2java->Analysis 然后输入四川省成都市动物园，得到是按照每个字的分词效果

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步骤 2 : 配置中文分词

接下来为 Solr 准备中文分词

步骤 3 : 下载 IKAnalyzer6.5.0.jar

从下载区(点击进入)下载 IKAnalyzer6.5.0.jar，然后复制到如下目录：

D:\software\solr-7.2.1\server\solr-webapp\webapp\WEB-INF\lib

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步骤 4 : 增加新的字段类型

修改配置文件 managed-schema：

D:\software\solr-7.2.1\server\solr\how2java\conf\managed-schema

在<schema...> 标签下增加如下代码

</fieldType>

下面贴出来完整的修改之后的，不放心的就直接复制完整的覆盖

D:\software\solr-7.2.1\server\solr\how2java\conf\managed-schema

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<?xml version="1.0" encoding="UTF-8" ?>

<!--

Licensed to the Apache Software Foundation (ASF) under one or more

contributor license agreements. See the NOTICE file distributed with

this work for additional information regarding copyright ownership.

The ASF licenses this file to You under the Apache License, Version 2.0

(the "License"); you may not use this file except in compliance with

the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software

distributed under the License is distributed on an "AS IS" BASIS,

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and

limitations under the License.

-->

<!--

This example schema is the recommended starting point for users.

It should be kept correct and concise, usable out-of-the-box.

For more information, on how to customize this file, please see

http://lucene.apache.org/solr/guide/documents-fields-and-schema-design.html

PERFORMANCE NOTE: this schema includes many optional features and should not

be used for benchmarking. To improve performance one could

- set stored="false" for all fields possible (esp large fields) when you

only need to search on the field but don't need to return the original

value.

- set indexed="false" if you don't need to search on the field, but only

return the field as a result of searching on other indexed fields.

- remove all unneeded copyField statements

- for best index size and searching performance, set "index" to false

for all general text fields, use copyField to copy them to the

catchall "text" field, and use that for searching.

-->

</fieldType>

<!-- attribute "name" is the name of this schema and is only used for display purposes.

version="x.y" is Solr's version number for the schema syntax and

semantics. It should not normally be changed by applications.

1.0: multiValued attribute did not exist, all fields are multiValued

by nature

1.1: multiValued attribute introduced, false by default

1.2: omitTermFreqAndPositions attribute introduced, true by default

except for text fields.

1.3: removed optional field compress feature

1.4: autoGeneratePhraseQueries attribute introduced to drive QueryParser

behavior when a single string produces multiple tokens. Defaults

to off for version >= 1.4

1.5: omitNorms defaults to true for primitive field types

(int, float, boolean, string...)

1.6: useDocValuesAsStored defaults to true.

-->

<!-- Valid attributes for fields:

name: mandatory - the name for the field

type: mandatory - the name of a field type from the

fieldTypes section

indexed: true if this field should be indexed (searchable or sortable)

stored: true if this field should be retrievable

docValues: true if this field should have doc values. Doc Values is

recommended (required, if you are using *Point fields) for faceting,

grouping, sorting and function queries. Doc Values will make the index

faster to load, more NRT-friendly and more memory-efficient.

They are currently only supported by StrField, UUIDField, all

*PointFields, and depending on the field type, they might require

the field to be single-valued, be required or have a default value

(check the documentation of the field type you're interested in for

more information)

multiValued: true if this field may contain multiple values per document

omitNorms: (expert) set to true to omit the norms associated with

this field (this disables length normalization and index-time

boosting for the field, and saves some memory). Only full-text

fields or fields that need an index-time boost need norms.

Norms are omitted for primitive (non-analyzed) types by default.

termVectors: [false] set to true to store the term vector for a

given field.

When using MoreLikeThis, fields used for similarity should be

stored for best performance.

termPositions: Store position information with the term vector.

This will increase storage costs.

termOffsets: Store offset information with the term vector. This

will increase storage costs.

required: The field is required. It will throw an error if the

value does not exist

default: a value that should be used if no value is specified

when adding a document.

-->

<!-- field names should consist of alphanumeric or underscore characters only and

not start with a digit. This is not currently strictly enforced,

but other field names will not have first class support from all components

and back compatibility is not guaranteed. Names with both leading and

trailing underscores (e.g. _version_) are reserved.

-->

<!-- In this _default configset, only four fields are pre-declared:

id, _version_, and _text_ and _root_. All other fields will be type guessed and added via the

"add-unknown-fields-to-the-schema" update request processor chain declared in solrconfig.xml.

Note that many dynamic fields are also defined - you can use them to specify a

field's type via field naming conventions - see below.

WARNING: The _text_ catch-all field will significantly increase your index size.

If you don't need it, consider removing it and the corresponding copyField directive.

-->

<!-- This can be enabled, in case the client does not know what fields may be searched. It isn't enabled by default

because it's very expensive to index everything twice. -->

<!-- Dynamic field definitions allow using convention over configuration

for fields via the specification of patterns to match field names.

EXAMPLE: name="*_i" will match any field ending in _i (like myid_i, z_i)

RESTRICTION: the glob-like pattern in the name attribute must have a "*" only at the start or the end. -->

<!-- Field to use to determine and enforce document uniqueness.

Unless this field is marked with required="false", it will be a required field

-->

<!-- copyField commands copy one field to another at the time a document

is added to the index. It's used either to index the same field differently,

or to add multiple fields to the same field for easier/faster searching.

-->

<!-- field type definitions. The "name" attribute is

just a label to be used by field definitions. The "class"

attribute and any other attributes determine the real

behavior of the fieldType.

Class names starting with "solr" refer to java classes in a

standard package such as org.apache.solr.analysis

-->

<!-- sortMissingLast and sortMissingFirst attributes are optional attributes are

currently supported on types that are sorted internally as strings

and on numeric types.

This includes "string", "boolean", "pint", "pfloat", "plong", "pdate", "pdouble".

- If sortMissingLast="true", then a sort on this field will cause documents

without the field to come after documents with the field,

regardless of the requested sort order (asc or desc).

- If sortMissingFirst="true", then a sort on this field will cause documents

without the field to come before documents with the field,

regardless of the requested sort order.

- If sortMissingLast="false" and sortMissingFirst="false" (the default),

then default lucene sorting will be used which places docs without the

field first in an ascending sort and last in a descending sort.

-->

<!--

Numeric field types that index values using KD-trees.

Point fields don't support FieldCache, so they must have docValues="true" if needed for sorting, faceting, functions, etc.

-->

<!-- The format for this date field is of the form 1995-12-31T23:59:59Z, and

is a more restricted form of the canonical representation of dateTime

http://www.w3.org/TR/xmlschema-2/#dateTime

The trailing "Z" designates UTC time and is mandatory.

Optional fractional seconds are allowed: 1995-12-31T23:59:59.999Z

All other components are mandatory.

Expressions can also be used to denote calculations that should be

performed relative to "NOW" to determine the value, ie...

NOW/HOUR

... Round to the start of the current hour

NOW-1DAY

... Exactly 1 day prior to now

NOW/DAY+6MONTHS+3DAYS

... 6 months and 3 days in the future from the start of

the current day

-->

<!-- solr.TextField allows the specification of custom text analyzers

specified as a tokenizer and a list of token filters. Different

analyzers may be specified for indexing and querying.

The optional positionIncrementGap puts space between multiple fields of

this type on the same document, with the purpose of preventing false phrase

matching across fields.

For more info on customizing your analyzer chain, please see

http://lucene.apache.org/solr/guide/understanding-analyzers-tokenizers-and-filters.html#understanding-analyzers-tokenizers-and-filters

-->

<!-- One can also specify an existing Analyzer class that has a

default constructor via the class attribute on the analyzer element.

Example:

</fieldType>

-->

</analyzer>

</fieldType>

<!-- A general text field that has reasonable, generic

cross-language defaults: it tokenizes with StandardTokenizer,

removes stop words from case-insensitive "stopwords.txt"

(empty by default), and down cases. At query time only, it

also applies synonyms.

-->

<!-- in this example, we will only use synonyms at query time

-->

</analyzer>

</analyzer>

</fieldType>

<!-- A text field with defaults appropriate for English: it tokenizes with StandardTokenizer,

removes English stop words (lang/stopwords_en.txt), down cases, protects words from protwords.txt, and

finally applies Porter's stemming. The query time analyzer also applies synonyms from synonyms.txt. -->

<!-- in this example, we will only use synonyms at query time

-->

<!-- Case insensitive stop word removal.

-->

<filter class="solr.StopFilterFactory"

ignoreCase="true"

words="lang/stopwords_en.txt"

<!-- Optionally you may want to use this less aggressive stemmer instead of PorterStemFilterFactory:

-->

</analyzer>

<filter class="solr.StopFilterFactory"

ignoreCase="true"

words="lang/stopwords_en.txt"

<!-- Optionally you may want to use this less aggressive stemmer instead of PorterStemFilterFactory:

-->

</analyzer>

</fieldType>

<!-- A text field with defaults appropriate for English, plus

aggressive word-splitting and autophrase features enabled.

This field is just like text_en, except it adds

WordDelimiterGraphFilter to enable splitting and matching of

words on case-change, alpha numeric boundaries, and

non-alphanumeric chars. This means certain compound word

cases will work, for example query "wi fi" will match

document "WiFi" or "wi-fi".

-->

<!-- in this example, we will only use synonyms at query time

-->

<!-- Case insensitive stop word removal.

-->

<filter class="solr.StopFilterFactory"

ignoreCase="true"

words="lang/stopwords_en.txt"

</analyzer>

<filter class="solr.StopFilterFactory"

ignoreCase="true"

words="lang/stopwords_en.txt"

</analyzer>

</fieldType>

<!-- Less flexible matching, but less false matches. Probably not ideal for product names,

but may be good for SKUs. Can insert dashes in the wrong place and still match. -->

<!-- this filter can remove any duplicate tokens that appear at the same position - sometimes

possible with WordDelimiterGraphFilter in conjuncton with stemming. -->

</analyzer>

<!-- this filter can remove any duplicate tokens that appear at the same position - sometimes

possible with WordDelimiterGraphFilter in conjuncton with stemming. -->

</analyzer>

</fieldType>

<!-- Just like text_general except it reverses the characters of

each token, to enable more efficient leading wildcard queries.

-->

<filter class="solr.ReversedWildcardFilterFactory" withOriginal="true"

maxPosAsterisk="3" maxPosQuestion="2" maxFractionAsterisk="0.33"/>

</analyzer>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

<!--

Example of using PathHierarchyTokenizerFactory at index time, so

queries for paths match documents at that path, or in descendent paths

-->

</analyzer>

</analyzer>

</fieldType>

<!--

Example of using PathHierarchyTokenizerFactory at query time, so

queries for paths match documents at that path, or in ancestor paths

-->

</analyzer>

</analyzer>

</fieldType>

<!-- This point type indexes the coordinates as separate fields (subFields)

If subFieldType is defined, it references a type, and a dynamic field

definition is created matching *___<typename>. Alternately, if

subFieldSuffix is defined, that is used to create the subFields.

Example: if subFieldType="double", then the coordinates would be

indexed in fields myloc_0___double,myloc_1___double.

Example: if subFieldSuffix="_d" then the coordinates would be indexed

in fields myloc_0_d,myloc_1_d

The subFields are an implementation detail of the fieldType, and end

users normally should not need to know about them.

-->

<!-- A geospatial field type that supports multiValued and polygon shapes.

For more information about this and other spatial fields see:

http://lucene.apache.org/solr/guide/spatial-search.html

-->

<fieldType name="location_rpt" class="solr.SpatialRecursivePrefixTreeFieldType"

geo="true" distErrPct="0.025" maxDistErr="0.001" distanceUnits="kilometers" />

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

<!-- Japanese using morphological analysis (see text_cjk for a configuration using bigramming)

NOTE: If you want to optimize search for precision, use default operator AND in your request

handler config (q.op) Use OR if you would like to optimize for recall (default).

-->

<!-- Kuromoji Japanese morphological analyzer/tokenizer (JapaneseTokenizer)

Kuromoji has a search mode (default) that does segmentation useful for search. A heuristic

is used to segment compounds into its parts and the compound itself is kept as synonym.

Valid values for attribute mode are:

normal: regular segmentation

search: segmentation useful for search with synonyms compounds (default)

extended: same as search mode, but unigrams unknown words (experimental)

For some applications it might be good to use search mode for indexing and normal mode for

queries to reduce recall and prevent parts of compounds from being matched and highlighted.

Use <analyzer type="index"> and <analyzer type="query"> for this and mode normal in query.

Kuromoji also has a convenient user dictionary feature that allows overriding the statistical

model with your own entries for segmentation, part-of-speech tags and readings without a need

to specify weights. Notice that user dictionaries have not been subject to extensive testing.

User dictionary attributes are:

userDictionary: user dictionary filename

userDictionaryEncoding: user dictionary encoding (default is UTF-8)

See lang/userdict_ja.txt for a sample user dictionary file.

Punctuation characters are discarded by default. Use discardPunctuation="false" to keep them.

-->

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

</analyzer>

</fieldType>

<!-- Similarity is the scoring routine for each document vs. a query.

A custom Similarity or SimilarityFactory may be specified here, but

the default is fine for most applications.

For more info: http://lucene.apache.org/solr/guide/other-schema-elements.html#OtherSchemaElements-Similarity

-->

<!--

<str name="paramkey">param value</str>

</similarity>

-->

</schema>

步骤 5 : 重启 Solr

使用如下命令重启

cd D:\software\solr-7.2.1\bin

solr.cmd stop -all

solr.cmd start

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步骤 6 : 重新测试分词

如图所示，使用中文分词后，就可以看到分词的效果了。
注： FieldType 记得选增加新的字段类型中的 text_ik

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搜索引擎技术系列教材（四）- solr - 设置字段

步骤 1 : 字段概念

创建Core 中的Core就相当于表，那么接下来就要为这个表设置字段，用于存放数据

步骤 2 : 创建name字段

左边选中 how2java -> Schema -> Add Field 输入name: name， field type: text_ik, 这里一定要使用中文分词中新创建的 text_ik类型，否则后续查询中文会失败。
然后点击 Add Field按钮进行添加

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步骤 3 : 创建其他字段

按照创建name字段的方式，继续创建如下字段：
category text_ik,
price pfloat,
place text_ik,
code text_ik
注： price的类型是pfloat

步骤 4 : 关于id字段

id字段是默认就有的，无需自己创建

步骤 5 : 查看创建的字段

创建好之后，可以看到如图所示的这些字段名。
为什么要有这些字段名呢？因为后续要加入索引的产品对象，就是这些字段名了

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搜索引擎技术系列教材（五）- solr - SolrJ 教程 - 使用 SolrJ 向 Solr 增加14万条索引记录

步骤 1 : 如何创建索引

solr 提供了一种方式向其中增加索引的界面，但是呢。。。不太方便，也和实际工作环境不相符合。
实际工作环境一般都是从数据库里读取数据，然后加入到索引的。很少会通过界面添加索引，因为这样维护更新删除也不方便，尤其是数据量比较大的时候。
那么本教材就会讲解，如何通过程序把数据加入到Solr 索引里。

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步骤 2 : SolrJ

Solr 支持通过各种各样的语言（如php,javascript, c#, ）把数据加入到索引里，因为本教程主要是基于Java的，所以会使用一个第三方工具SolrJ，使用 Java 语言来把数据加入到索引里。

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步骤 3 : 先运行，看到效果，再学习

老规矩，先下载下载区(点击进入)的可运行项目，配置运行起来，确认可用之后，再学习做了哪些步骤以达到这样的效果。
下载右上角的solr4j.rar, 然后运行里面的 TestSolr4j，一共导入14万条数据，时间比较长，请耐心等待。
完成之后，打开

http://127.0.0.1:8983/solr/#/how2java

左边点击 Query -> 点击 Execute Query 查询之后，可以看到右侧显示查询结果，总数是 147939 条

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步骤 4 : 模仿和排错

在确保可运行项目能够正确无误地运行之后，再严格照着教程的步骤，对代码模仿一遍。
模仿过程难免代码有出入，导致无法得到期望的运行结果，此时此刻通过比较正确答案 ( 可运行项目 ) 和自己的代码，来定位问题所在。
采用这种方式，学习有效果，排错有效率，可以较为明显地提升学习速度，跨过学习路上的各个槛。

推荐使用diffmerge软件，进行文件夹比较。把你自己做的项目文件夹，和我的可运行项目文件夹进行比较。
这个软件很牛逼的，可以知道文件夹里哪两个文件不对，并且很明显地标记出来
这里提供了绿色安装和使用教程：diffmerge 下载和使用教程

步骤 5 : 14万条数据

为了模仿真实环境，花了很多精力，四处搜刮来了14万条天猫的产品数据，接下来我们就会把这14万条记录加入到 Solr,然后观察搜索效果。
这14万条记录放在下载区(点击进入) 140k_products.rar，其解析办法在后续会讲解

步骤 6 : 关于数据库

本来应该先把这14万条记录保存进数据库，然后再从数据库中取出来的，不过考虑到不是每个同学都有JDBC基础，以及放进数据库的繁琐，和14万条数据从数据库里读取出来的时间消耗，就改成直接从文件里读取出来，然后转换为泛型是Product的集合的形式，相当于从数据库里读取出来了，不过会快很多。

步骤 7 : 140k_products.txt

首先下载 140k_products.rar,并解压为140k_products.txt，然后放在项目目录下。这个文件里一共有14万条产品记录。

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步骤 8 : Product.java

准备实体类来存放产品信息
注：每个字段上都有@Field 注解，用来告诉Solr 这些和 how2java core里的字段对应

package how2java;

import org.apache.solr.client.solrj.beans.Field;

public class Product {

@Field

int id;

@Field

String name;

@Field

String category;

@Field

float price;

@Field

String place;

@Field

String code;

public int getId() {

return id;

}

public void setId(int id) {

this.id = id;

}

public String getName() {

return name;

}

public void setName(String name) {

this.name = name;

}

public String getCategory() {

return category;

}

public void setCategory(String category) {

this.category = category;

}

public float getPrice() {

return price;

}

public void setPrice(float price) {

this.price = price;

}

public String getPlace() {

return place;

}

public void setPlace(String place) {

this.place = place;

}

public String getCode() {

return code;

}

public void setCode(String code) {

this.code = code;

}

@Override

public String toString() {

return "Product [id=" + id + ", name=" + name + ", category=" + category + ", price=" + price + ", place="

+ place + ", code=" + code + "]";

}

步骤 9 : ProductUtil

工具类，把 140k_products.txt 文本文件，转换为泛型是Product的集合

package how2java;

import java.awt.AWTException;

import java.io.File;

import java.io.IOException;

import java.util.ArrayList;

import java.util.List;

import org.apache.commons.io.FileUtils;

public class ProductUtil {

public static void main(String[] args) throws IOException, InterruptedException, AWTException {

String fileName = "140k_products.txt";

List<Product> products = file2list(fileName);

System.out.println(products.size());

}

public static List<Product> file2list(String fileName) throws IOException {

File f = new File(fileName);

List<String> lines = FileUtils.readLines(f,"UTF-8");

List<Product> products = new ArrayList<>();

for (String line : lines) {

Product p = line2product(line);

products.add(p);

}

return products;

}

private static Product line2product(String line) {

Product p = new Product();

String[] fields = line.split(",");

p.setId(Integer.parseInt(fields[0]));

p.setName(fields[1]);

p.setCategory(fields[2]);

p.setPrice(Float.parseFloat(fields[3]));

p.setPlace(fields[4]);

p.setCode(fields[5]);

return p;

}

步骤 10 : SolrUtil

工具类，用来把产品集合批量增加到Solr. 这里就用到了SolrJ第三方包里的api了。

package how2java;

import java.io.IOException;

import java.util.List;

import org.apache.solr.client.solrj.SolrClient;

import org.apache.solr.client.solrj.SolrServerException;

import org.apache.solr.client.solrj.beans.DocumentObjectBinder;

import org.apache.solr.client.solrj.impl.HttpSolrClient;

import org.apache.solr.common.SolrInputDocument;

public class SolrUtil {

public static SolrClient client;

private static String url;

static {

url = "http://localhost:8983/solr/how2java";

client = new HttpSolrClient.Builder(url).build();

}

public static <T> boolean batchSaveOrUpdate(List<T> entities) throws SolrServerException, IOException {

DocumentObjectBinder binder = new DocumentObjectBinder();

int total = entities.size();

int count=0;

for (T t : entities) {

SolrInputDocument doc = binder.toSolrInputDocument(t);

client.add(doc);

System.out.printf("添加数据到索引中，总共要添加 %d 条记录，当前添加第%d条 %n",total,++count);

}

client.commit();

return true;

}

步骤 11 : TestSolr4j

得到14万个产品对象，然后通过SolrUtil 工具类提交到Solr 服务器

package how2java;

import java.io.IOException;

import java.util.List;

import org.apache.solr.client.solrj.SolrServerException;

public class TestSolr4j {

public static void main(String[] args) throws SolrServerException, IOException {

List<Product> products = ProductUtil.file2list("140k_products.txt");

SolrUtil.batchSaveOrUpdate(products);

}

步骤 12 : 验证提交效果

打开

http://127.0.0.1:8983/solr/#/how2java

左边点击 Query -> 点击 Execute Query 查询之后，可以看到右侧显示查询结果，总数是 147939 条

最全面solrr入门教程 - 文章图片

搜索引擎技术系列教材（六）- solr - SolrJ 分页查询

步骤 1 : 先运行，看到效果，再学习

老规矩，先下载下载区(点击进入)的可运行项目，配置运行起来，确认可用之后，再学习做了哪些步骤以达到这样的效果。
运行TestSolr4j，可以看到如图所示的查询了10条出来的效果

最全面solrr入门教程 - 文章图片

步骤 2 : 模仿和排错

步骤 3 : SolrUtil

SolrUtil 增加分页查询的方法

public static QueryResponse query(String keywords,int startOfPage, int numberOfPage) throwsSolrServerException, IOException {

SolrQuery query = new SolrQuery();

query.setStart(startOfPage);

query.setRows(numberOfPage);

query.setQuery(keywords);

QueryResponse rsp = client.query(query);

return rsp;

}

package how2java;

import java.io.IOException;

import java.util.List;

import org.apache.solr.client.solrj.SolrClient;

import org.apache.solr.client.solrj.SolrQuery;

import org.apache.solr.client.solrj.SolrServerException;

import org.apache.solr.client.solrj.beans.DocumentObjectBinder;

import org.apache.solr.client.solrj.impl.HttpSolrClient;

import org.apache.solr.client.solrj.response.QueryResponse;

import org.apache.solr.common.SolrDocument;

import org.apache.solr.common.SolrDocumentList;

import org.apache.solr.common.SolrInputDocument;

import org.apache.solr.common.util.NamedList;

public class SolrUtil {

public static SolrClient client;

private static String url;

static {

url = "http://localhost:8983/solr/how2java";

client = new HttpSolrClient.Builder(url).build();

}

public static <T> boolean batchSaveOrUpdate(List<T> entities) throws SolrServerException, IOException {

DocumentObjectBinder binder = new DocumentObjectBinder();

int total = entities.size();

int count=0;

for (T t : entities) {

SolrInputDocument doc = binder.toSolrInputDocument(t);

client.add(doc);

System.out.printf("添加数据到索引中，总共要添加 %d 条记录，当前添加第%d条 %n",total,++count);

}

client.commit();

return true;

}

public static QueryResponse query(String keywords,int startOfPage, int numberOfPage) throwsSolrServerException, IOException {

SolrQuery query = new SolrQuery();

query.setStart(startOfPage);

query.setRows(numberOfPage);

query.setQuery(keywords);

QueryResponse rsp = client.query(query);

return rsp;

}

步骤 4 : TestSolr4j

拿到分页查询的结果，遍历出来

package how2java;

import java.io.IOException;

import java.util.Collection;

import org.apache.solr.client.solrj.SolrServerException;

import org.apache.solr.client.solrj.response.QueryResponse;

import org.apache.solr.common.SolrDocument;

import org.apache.solr.common.SolrDocumentList;

public class TestSolr4j {

public static void main(String[] args) throws SolrServerException, IOException {

//查询

QueryResponse queryResponse = SolrUtil.query("name:手机",0,10);

SolrDocumentList documents= queryResponse.getResults();

System.out.println("累计找到的条数："+documents.getNumFound());

if(!documents.isEmpty()){

Collection<String> fieldNames = documents.get(0).getFieldNames();

for (String fieldName : fieldNames) {

System.out.print(fieldName+"\t");

}

System.out.println();

}

for (SolrDocument solrDocument : documents) {

Collection<String> fieldNames= solrDocument.getFieldNames();

for (String fieldName : fieldNames) {

System.out.print(solrDocument.get(fieldName)+"\t");

}

System.out.println();

}

搜索引擎技术系列教材（七）- solr - SolrJ 高亮显示

步骤 1 : 先运行，看到效果，再学习

老规矩，先下载下载区(点击进入)的可运行项目，配置运行起来，确认可用之后，再学习做了哪些步骤以达到这样的效果。
运行TestSolr4j 看到如图所示的效果，手机这个关键字被高亮出来了

最全面solrr入门教程 - 文章图片

步骤 2 : 模仿和排错

步骤 3 : SolrUtil

增加queryHighlight 方法

public static void queryHighlight(String keywords) throws SolrServerException, IOException {

SolrQuery q = new SolrQuery();

//开始页数

q.setStart(0);

//每页显示条数

q.setRows(10);

// 设置查询关键字

q.setQuery(keywords);

// 开启高亮

q.setHighlight(true);

// 高亮字段

q.addHighlightField("name");

// 高亮单词的前缀

q.setHighlightSimplePre("");

// 高亮单词的后缀

q.setHighlightSimplePost("");

//摘要最长100个字符

q.setHighlightFragsize(100);

//查询

QueryResponse query = client.query(q);

//获取高亮字段name相应结果

NamedList<Object> response = query.getResponse();

NamedList<?> highlighting = (NamedList<?>) response.get("highlighting");

for (int i = 0; i < highlighting.size(); i++) {

System.out.println(highlighting.getName(i) + "：" + highlighting.getVal(i));

}

//获取查询结果

SolrDocumentList results = query.getResults();

for (SolrDocument result : results) {

System.out.println(result.toString());

}

package how2java;

import java.io.IOException;

import java.util.List;

import org.apache.solr.client.solrj.SolrClient;

import org.apache.solr.client.solrj.SolrQuery;

import org.apache.solr.client.solrj.SolrServerException;

import org.apache.solr.client.solrj.beans.DocumentObjectBinder;

import org.apache.solr.client.solrj.impl.HttpSolrClient;

import org.apache.solr.client.solrj.response.QueryResponse;

import org.apache.solr.common.SolrDocument;

import org.apache.solr.common.SolrDocumentList;

import org.apache.solr.common.SolrInputDocument;

import org.apache.solr.common.util.NamedList;

public class SolrUtil {

public static SolrClient client;

private static String url;

static {

url = "http://localhost:8983/solr/how2java";

client = new HttpSolrClient.Builder(url).build();

}

public static void queryHighlight(String keywords) throws SolrServerException, IOException {

SolrQuery q = new SolrQuery();

//开始页数

q.setStart(0);

//每页显示条数

q.setRows(10);

// 设置查询关键字

q.setQuery(keywords);

// 开启高亮

q.setHighlight(true);

// 高亮字段

q.addHighlightField("name");

// 高亮单词的前缀

q.setHighlightSimplePre("");

// 高亮单词的后缀

q.setHighlightSimplePost("");

//摘要最长100个字符

q.setHighlightFragsize(100);

//查询

QueryResponse query = client.query(q);

//获取高亮字段name相应结果

NamedList<Object> response = query.getResponse();

NamedList<?> highlighting = (NamedList<?>) response.get("highlighting");

for (int i = 0; i < highlighting.size(); i++) {

System.out.println(highlighting.getName(i) + "：" + highlighting.getVal(i));

}

//获取查询结果

SolrDocumentList results = query.getResults();

for (SolrDocument result : results) {

System.out.println(result.toString());

}

public static <T> boolean batchSaveOrUpdate(List<T> entities) throws SolrServerException, IOException {

DocumentObjectBinder binder = new DocumentObjectBinder();

int total = entities.size();

int count=0;

for (T t : entities) {

SolrInputDocument doc = binder.toSolrInputDocument(t);

client.add(doc);

System.out.printf("添加数据到索引中，总共要添加 %d 条记录，当前添加第%d条 %n",total,++count);

}

client.commit();

return true;

}

public static QueryResponse query(String keywords,int startOfPage, int numberOfPage) throwsSolrServerException, IOException {

SolrQuery query = new SolrQuery();

query.setStart(startOfPage);

query.setRows(numberOfPage);

query.setQuery(keywords);

QueryResponse rsp = client.query(query);

return rsp;

}

步骤 4 : TestSolr4j

调用queryHighlight 方法

package how2java;

import java.io.IOException;

import org.apache.solr.client.solrj.SolrServerException;

public class TestSolr4j {

public static void main(String[] args) throws SolrServerException, IOException {

//高亮查询查询

SolrUtil.queryHighlight("name:手机");

}

搜索引擎技术系列教材（八）- solr - SolrJ 更新和删除索引

步骤 1 : 先运行，看到效果，再学习

老规矩，先下载下载区(点击进入)的可运行项目，配置运行起来，确认可用之后，再学习做了哪些步骤以达到这样的效果。
运行TestSolr4j就可以看到在修改之前使用关键字鞭能查询到一条结果，修改之后，查询的结果改变了。删除之后，查询不到结果了

最全面solrr入门教程 - 文章图片

步骤 2 : 模仿和排错

步骤 3 : SolrUtil

SolrUtil提供一个对象的增加或者更新(都是同一个方法）

public static <T> boolean saveOrUpdate(T entity) throws SolrServerException, IOException {

DocumentObjectBinder binder = new DocumentObjectBinder();

SolrInputDocument doc = binder.toSolrInputDocument(entity);

client.add(doc);

client.commit();

return true;

}

根据id删除这个索引

public static boolean deleteById(String id) {

try {

client.deleteById(id);

client.commit();

} catch (Exception e) {

e.printStackTrace();

return false;

}

return true;

}

package how2java;

import java.io.IOException;

import java.util.List;

import org.apache.solr.client.solrj.SolrClient;

import org.apache.solr.client.solrj.SolrQuery;

import org.apache.solr.client.solrj.SolrServerException;

import org.apache.solr.client.solrj.beans.DocumentObjectBinder;

import org.apache.solr.client.solrj.impl.HttpSolrClient;

import org.apache.solr.client.solrj.response.QueryResponse;

import org.apache.solr.common.SolrDocument;

import org.apache.solr.common.SolrDocumentList;

import org.apache.solr.common.SolrInputDocument;

import org.apache.solr.common.util.NamedList;

public class SolrUtil {

public static SolrClient client;

private static String url;

static {

url = "http://localhost:8983/solr/how2java";

client = new HttpSolrClient.Builder(url).build();

}

public static void queryHighlight(String keywords) throws SolrServerException, IOException {

SolrQuery q = new SolrQuery();

//开始页数

q.setStart(0);

//每页显示条数

q.setRows(10);

// 设置查询关键字

q.setQuery(keywords);

// 开启高亮

q.setHighlight(true);

// 高亮字段

q.addHighlightField("name");

// 高亮单词的前缀

q.setHighlightSimplePre("");

// 高亮单词的后缀

q.setHighlightSimplePost("");

//摘要最长100个字符

q.setHighlightFragsize(100);

//查询

QueryResponse query = client.query(q);

//获取高亮字段name相应结果

NamedList<Object> response = query.getResponse();

NamedList<?> highlighting = (NamedList<?>) response.get("highlighting");

for (int i = 0; i < highlighting.size(); i++) {

System.out.println(highlighting.getName(i) + "：" + highlighting.getVal(i));

}

//获取查询结果

SolrDocumentList results = query.getResults();

for (SolrDocument result : results) {

System.out.println(result.toString());

}

public static <T> boolean batchSaveOrUpdate(List<T> entities) throws SolrServerException, IOException {

DocumentObjectBinder binder = new DocumentObjectBinder();

int total = entities.size();

int count=0;

for (T t : entities) {

SolrInputDocument doc = binder.toSolrInputDocument(t);

client.add(doc);

System.out.printf("添加数据到索引中，总共要添加 %d 条记录，当前添加第%d条 %n",total,++count);

}

client.commit();

return true;

}

public static QueryResponse query(String keywords,int startOfPage, int numberOfPage) throwsSolrServerException, IOException {

SolrQuery query = new SolrQuery();

query.setStart(startOfPage);

query.setRows(numberOfPage);

query.setQuery(keywords);

QueryResponse rsp = client.query(query);

return rsp;

}

public static <T> boolean saveOrUpdate(T entity) throws SolrServerException, IOException {

DocumentObjectBinder binder = new DocumentObjectBinder();

SolrInputDocument doc = binder.toSolrInputDocument(entity);

client.add(doc);

client.commit();

return true;

}

public static boolean deleteById(String id) {

try {

client.deleteById(id);

client.commit();

} catch (Exception e) {

e.printStackTrace();

return false;

}

return true;

}

步骤 4 : TestSolr4j

修改之前查询一次
修改之后查询一次
删除之后查询一次
观察修改和删除的效果

最全面solrr入门教程 - 文章图片

package how2java;

import java.io.IOException;

import java.util.Collection;

import java.util.List;

import org.apache.solr.client.solrj.SolrServerException;

import org.apache.solr.client.solrj.response.QueryResponse;

import org.apache.solr.common.SolrDocument;

import org.apache.solr.common.SolrDocumentList;

public class TestSolr4j {

public static void main(String[] args) throws SolrServerException, IOException {

String keyword = "name:鞭";

System.out.println("修改之前");

query(keyword);

Product p = new Product();

p.setId(51173);

p.setName("修改后的神鞭");

SolrUtil.saveOrUpdate(p);

System.out.println("修改之后");

query(keyword);

SolrUtil.deleteById("51173");

System.out.println("删除之后");

query(keyword);

}

private static void query(String keyword) throws SolrServerException, IOException {

QueryResponse queryResponse = SolrUtil.query(keyword,0,10);

SolrDocumentList documents= queryResponse.getResults();

System.out.println("累计找到的条数："+documents.getNumFound());

if(!documents.isEmpty()){

Collection<String> fieldNames = documents.get(0).getFieldNames();

for (String fieldName : fieldNames) {

System.out.print(fieldName+"\t");

}

System.out.println();

}

for (SolrDocument solrDocument : documents) {

Collection<String> fieldNames= solrDocument.getFieldNames();

for (String fieldName : fieldNames) {

System.out.print(solrDocument.get(fieldName)+"\t");

}

System.out.println();

}

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首页 / SOLR / 最全面solrr入门教程

最全面solrr入门教程

内容导读

内容图文

搜索引擎技术系列教材（一）- solr - Solr 入门教程

搜索引擎技术系列教材（二）- solr - 创建Core

搜索引擎技术系列教材（三）- solr - Solr7.2 可以用的中文分词器 IKAnalyzer6.5.0.jar

搜索引擎技术系列教材（四）- solr - 设置字段

搜索引擎技术系列教材（五）- solr - SolrJ 教程 - 使用 SolrJ 向 Solr 增加14万条索引记录

搜索引擎技术系列教材（六）- solr - SolrJ 分页查询

搜索引擎技术系列教材（七）- solr - SolrJ 高亮显示

搜索引擎技术系列教材（八）- solr - SolrJ 更新和删除索引

内容总结

内容备注

内容手机端

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