跟益达学Solr5之批量索引JSON数据

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        假定你有这样一堆JSON数据，

 

[
  {"id":"1", "name":"Red Lobster", "city":"San Francisco, CA", "type":"Sit-down Chain", "state":"California", "tags":["sea food", "sit down"], "price":33.00},
  {"id":"2", "name":"Red Lobster", "city":"Atlanta, GA", "type":"Sit-down Chain", "state":"Georgia", "tags":["sea food", "sit-down"], "price":22.00},
  {"id":"3", "name":"Red Lobster", "city":"New York, NY", "type":"Sit-down Chain", "state":"New York", "tags":["sea food", "sit-down"], "price":29.00},
  {"id":"4", "name":"McDonalds", "city":"San Francisco, CA", "type":"Fast Food", "state":"California", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":9.00},
  {"id":"5", "name":"McDonalds", "city":"Atlanta, GA", "type":"Fast Food", "state":"Georgia", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00},
  {"id":"6", "name":"McDonalds", "city":"New York, NY", "type":"Fast Food", "state":"New York", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00},
  {"id":"7", "name":"McDonalds", "city":"Chicago, IL", "type":"Fast Food", "state":"Illinois", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00},
  {"id":"8", "name":"McDonalds", "city":"Austin, TX", "type":"Fast Food", "state":"Texas", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00},
  {"id":"9", "name":"Pizza Hut", "city":"Atlanta, GA", "type":"Sit-down Chain", "state":"Georgia", "tags":["pizza", "sit-down", "delivery"], "price":15.00},
  {"id":"10", "name":"Pizza Hut", "city":"New York, NY", "type":"Sit-down Chain", "state":"New York", "tags":["pizza", "sit-down", "delivery"], "price":24.00},
  {"id":"11", "name":"Pizza Hut", "city":"Austin, TX", "type":"Sit-down Chain", "state":"Texas", "tags":["pizza", "sit-down", "delivery"], "price":18.00},
  {"id":"12", "name":"Freddy's Pizza Shop", "city":"Los Angeles, CA", "type":"Local Sit-down", "state":"California", "tags":["pizza", "pasta", "sit-down"], "price":25.00},
  {"id":"13", "name":"The Iberian Pig", "city":"Atlanta, GA", "type":"Upscale", "state":"Georgia", "tags":["spanish", "tapas", "sit-down", "upscale"], "price":45.00},
  {"id":"14", "name":"Sprig", "city":"Atlanta, GA", "type":"Local Sit-down", "state":"Georgia", "tags":["sit-down", "gluten-free", "southern cuisine"], "price":15.00},
  {"id":"15", "name":"Starbucks", "city":"San Francisco, CA", "type":"Coffee Shop", "state":"California", "tags":["coffee", "breakfast"], "price":7.50},
  {"id":"16", "name":"Starbucks", "city":"Atlanta, GA", "type":"Coffee Shop", "state":"Georgia", "tags":["coffee", "breakfast"], "price":4.00},
  {"id":"17", "name":"Starbucks", "city":"New York, NY", "type":"Coffee Shop", "state":"New York", "tags":["coffee", "breakfast"], "price":6.50},
  {"id":"18", "name":"Starbucks", "city":"Chicago, IL", "type":"Coffee Shop", "state":"Illinois", "tags":["coffee", "breakfast"], "price":6.00},
  {"id":"19", "name":"Starbucks", "city":"Austin, TX", "type":"Coffee Shop", "state":"Texas", "tags":["coffee", "breakfast"], "price":5.00},
  {"id":"20", "name":"Starbucks", "city":"Greenville, SC", "type":"Coffee Shop", "state":"South Carolina", "tags":["coffee", "breakfast"], "price":3.00}
]

   你想导入到Solr中进行索引，怎么办？其实Solr的Web UI界面就可以操作，在左侧有个Documents菜单，表示导入Document(当然也支持Document更新)的意思，Document加个s即表示支持批量导入多个Document，如图：

 Document Type即表示你的Document数据来源是什么，是来自于JSON，来自于XML,来自于CVS等等，

 

 Commit Within表示document提交必须在指定的毫秒数内完成，否则提交操作视为超时；

 Overwriter即表示是否覆盖索引目录下已有的索引数据，设置为false即表示不覆盖已有索引只在原来的基础上追加索引数据；

 Boost:表示设置Document的权重，默认值为1.0；

 如果你只是单个JSON对象需要导入，那直接选择Document Type为JSON即可，当你选择Document Type为JSON后，Document(s)文本框会提示一个示例，如图：

 当然你也可以选择Document Type为Solr Command(raw XML or JSON),只不过这时候JSON数据格式就有特殊要求了，你的JSON数据格式需要这样定义：

{
    "add": {
        "doc": {.......}
    },
    "add": {
        "doc": {.......}
    },
    "add": {
        "doc": {.......}
    },
    "add": {
        "doc": {.......}
    },
    "add": {
        "doc": {.......}
    },
   ............. and so on.
}

    其中{.........}部分就是你的Document对象，其余部分为固定格式。使用这种格式正好弥补了Document Type为JSON这种方式只能一条一条的导入，效率太低，当你需要批量导入多个Document时，采用这种格式支持批量导入多个Document。

 

    如果你需要导入XML数据，你需要选择Document Type为XML,如图：

 标签之间的就是你的XML数据，不过它跟Document Type选择为JSON有同样的弊端就是只支持单条导入，如果你需要批量导入XML数据，你同样可以选择Document Type为Solr Command(raw XML or JSON)，只不过这时候，数据格式应该是类似这样的：

    
        xxxx
        xxxxxxxx
        xxxxxxxx
    
    
    
        xxxx
        xxxxxxxx
        xxxxxxxx
    

    
        xxxx
        xxxxxxxx
        xxxxxxxx
    
    
    ............ and so on

    如果你想更新Document,那就把元素改成即可，同理还有你懂的，先前在讲post.jar的时候我有提到过，具体请参阅《跟益达学Solr5之玩转post.jar》,OK,说了那么多，那现在我就以JSON数据为例进行一个操作示范，假定我有这样一个JSON数据，如图：

     首先我们需要从JSON数据中提炼出Field域，并在我们的Schema.xml配置文件定义域，如图：

   然后我们需要把传统的JSON数据转换成Solr能识别的格式，如图：

{
	"add": {
		"doc": {"id":"1", "name":"Red Lobster", "city":"San Francisco, CA", "type":"Sit-down Chain", "state":"California", "tags":["sea food", "sit down"], "price":33.00}
	},
	"add": {
		"doc": {"id":"2", "name":"Red Lobster", "city":"Atlanta, GA", "type":"Sit-down Chain", "state":"Georgia", "tags":["sea food", "sit-down"], "price":22.00}
	},
	"add": {
		"doc": {"id":"3", "name":"Red Lobster", "city":"New York, NY", "type":"Sit-down Chain", "state":"New York", "tags":["sea food", "sit-down"], "price":29.00}
	},
	"add": {
		"doc": {"id":"4", "name":"McDonalds", "city":"San Francisco, CA", "type":"Fast Food", "state":"California", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":9.00}
	},
	"add": {
		"doc": {"id":"5", "name":"McDonalds", "city":"Atlanta, GA", "type":"Fast Food", "state":"Georgia", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00}
	},
	"add": {
		"doc": {"id":"6", "name":"McDonalds", "city":"New York, NY", "type":"Fast Food", "state":"New York", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00}
	},
	"add": {
		"doc": {"id":"7", "name":"McDonalds", "city":"Chicago, IL", "type":"Fast Food", "state":"Illinois", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00}
	},
	"add": {
		"doc": {"id":"8", "name":"McDonalds", "city":"Austin, TX", "type":"Fast Food", "state":"Texas", "tags":["fast food", "hamburgers", "coffee", "wi-fi", "breakfast"], "price":4.00}
	},
	"add": {
		"doc": {"id":"9", "name":"Pizza Hut", "city":"Atlanta, GA", "type":"Sit-down Chain", "state":"Georgia", "tags":["pizza", "sit-down", "delivery"], "price":15.00}
	},
	"add": {
		"doc": {"id":"10", "name":"Pizza Hut", "city":"New York, NY", "type":"Sit-down Chain", "state":"New York", "tags":["pizza", "sit-down", "delivery"], "price":24.00}
	},
	"add": {
		"doc": {"id":"11", "name":"Pizza Hut", "city":"Austin, TX", "type":"Sit-down Chain", "state":"Texas", "tags":["pizza", "sit-down", "delivery"], "price":18.00}
	},
	"add": {
		"doc": {"id":"12", "name":"Freddy's Pizza Shop", "city":"Los Angeles, CA", "type":"Local Sit-down", "state":"California", "tags":["pizza", "pasta", "sit-down"], "price":25.00}
	},
	"add": {
		"doc": {"id":"13", "name":"The Iberian Pig", "city":"Atlanta, GA", "type":"Upscale", "state":"Georgia", "tags":["spanish", "tapas", "sit-down", "upscale"], "price":45.00}
	},
	"add": {
		"doc": {"id":"14", "name":"Sprig", "city":"Atlanta, GA", "type":"Local Sit-down", "state":"Georgia", "tags":["sit-down", "gluten-free", "southern cuisine"], "price":15.00}
	},
	"add": {
		"doc": {"id":"15", "name":"Starbucks", "city":"San Francisco, CA", "type":"Coffee Shop", "state":"California", "tags":["coffee", "breakfast"], "price":7.50}
	},
	"add": {
		"doc": {"id":"16", "name":"Starbucks", "city":"Atlanta, GA", "type":"Coffee Shop", "state":"Georgia", "tags":["coffee", "breakfast"], "price":4.00}
	},
	"add": {
		"doc": {"id":"17", "name":"Starbucks", "city":"New York, NY", "type":"Coffee Shop", "state":"New York", "tags":["coffee", "breakfast"], "price":6.50}
	},
	"add": {
		"doc": {"id":"18", "name":"Starbucks", "city":"Chicago, IL", "type":"Coffee Shop", "state":"Illinois", "tags":["coffee", "breakfast"], "price":6.00}
	},
	"add": {
		"doc": {"id":"19", "name":"Starbucks", "city":"Austin, TX", "type":"Coffee Shop", "state":"Texas", "tags":["coffee", "breakfast"], "price":5.00}
	},
	"add": {
		"doc": {"id":"20", "name":"Starbucks", "city":"Greenville, SC", "type":"Coffee Shop", "state":"South Carolina", "tags":["coffee", "breakfast"], "price":3.00}
	}
}

    然后启动你的Tomcat，然后如图操作：

 

    提交后，执行查询，如图：

 as

   请注意Document Type选择项，如果你选择为JSON，那你将会收到这样一个异常，如图： 

    示例相关的配置以及测试数据，请看底下的附件，如果你们在操作过程中，遇到任何问题，请联系我，同时也欢迎各路Java高手加群一起交流学习，

   益达Q-Q:                7-3-6-0-3-1-3-0-5

 

   益达的Q-Q群：      1-0-5-0-9-8-8-0-6

 

 

   

 

 

   

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