初始化
$hosts = array('192.168.30.41'); $this->client = ElasticsearchClientBuilder::create()->setHosts($hosts)->build();
新建和设置index
$params = [ 'index' => 'order', 'body' => [ 'settings' => [ 'max_result_window' => 10000000 #由于默认只能读取前10000条数据,这里设置为100w,但是代价就是分页越靠后,效率越低。也可以使用scan解决 ], 'mappings' => [ 'goods' => [ '_source' => [ 'enabled' => true ], 'properties' => [ 'product_code' => [ 'type'=>'string', 'store'=>'yes', 'fielddata'=>true, 'fields'=>[ 'raw'=>[ #由于需要按照这个字段分组统计,且不能进行分词,固这样配置。统计时字段需要写为 product_code.raw 'type'=>'string', 'index'=>'not_analyzed' ] ] ], 'order_id'=>[ 'fielddata'=>true, 'type'=>'string' ], 'price'=>[ 'type'=>'double' ], 'num'=>[ 'type'=>'integer' ], 'pay_time'=>[ 'type'=>'date', 'format'=>'yyyy-MM-dd HH:mm:ss' ], 'take_province'=>[ 'type'=>'string', 'fielddata'=>true, 'store'=>'yes', 'fields'=>[ 'raw'=>[ 'type'=>'string', 'index'=>'not_analyzed' ] ] ], 'buyer_nike'=>[ 'type'=>'string', 'fielddata'=>true ] ] ] ] ] ]; $response = $this->client->indices()->create($params);
插入数据(这里引用了官方文档的例子,大数据导入不使用insert,而使用更为效率的bulk)
$params = ['body' => []]; for ($i = 1; $i <= 1234567; $i++) { $params['body'][] = [ 'index' => [ '_index' => 'my_index', '_type' => 'my_type', '_id' => $i ] ]; $params['body'][] = [ 'my_field' => 'my_value', 'second_field' => 'some more values' ]; // Every 1000 documents stop and send the bulk request if ($i % 1000 == 0) { $responses = $client->bulk($params); // erase the old bulk request $params = ['body' => []]; // unset the bulk response when you are done to save memory unset($responses); } } // Send the last batch if it exists if (!empty($params['body'])) { $responses = $client->bulk($params); }
相关查询
1、查询某商品某时间段内订单数、售卖总数和总价格
#where product_code="xxx" and pay_time BETWEEN "2017-01-01 00:00:00" AND "2017-01-31 23:59:59" $params = [ 'index' => 'order', 'type' => 'goods', 'body' => [ 'size' => 1, 'query' => [ "bool"=>[ "must"=>[ "term"=>["product_code.raw"=>$code] #上面解释过了,这里采用不分词的统计,使用字段.raw ], "filter"=>[ "range"=>[ "pay_time"=>[ "gte"=>$start_time, "lte"=>$end_time ] ] ] ] ], 'aggs' => [ 'sum_this_product'=>['sum'=>['field'=>"num"]], #售卖总数量,sum累加 'total_price'=>['sum'=>['field'=>"price"]], #总价格 'distinct_orderid'=>['cardinality'=>['field'=>'order_id']] #去重订单数 ] ] ]; $response = $this->client->search($params);
2、统计某时间段所有商品的订单数、售卖总数和总价格
#where pay_time BETWEEN "2017-01-01 00:00:00" AND "2017-01-31 23:59:59" $params = [ 'index' => 'order', 'type' => 'goods', 'body' => [ 'size' => 0, 'query' => [ "bool"=>[ "filter"=>[ "range"=>[ "pay_time"=>[ "gte"=>$start_time, "lte"=>$end_time ] ] ] ] ], 'aggs' => [ 'num'=>[ 'terms'=>[ 'field'=>'product_code.raw', 'size'=>100, 'order'=>['sum_this_product'=>'desc'] #根据统计出来的售卖总数排序 ], 'aggs'=>[ 'sum_this_product'=>['sum'=>['field'=>'num']], 'total_this_product'=>['sum'=>['field'=>'price']], 'distinct_orderid'=>['cardinality'=>['field'=>'order_id']] ] ] ] ] ]; $response = $this->client->search($params);
唠叨:
1、这次使用的是docker环境,使用阿里镜像:https://dev.aliyun.com/detail.html?spm=5176.1972343.2.21.F0KOV2&repoId=1209
2、官方文档:https://www.elastic.co/guide/en/elasticsearch/client/php-api/current/index.html
3、本次工作数据量大约1500w,需要复杂的统计和展现,mysql已经不能满足,故使用es。但是es不支持类似mysql:select in select这样的子查询,着实折腾了不少时间
4、感谢一位大神的博客:https://segmentfault.com/a/1190000004433446,这是个文章系列,很值得参考。