ElasticSearch7.3學習(二十九)----聚合實戰之使用Java api實現電視案例
2022-05-28 12:03:19
一、資料準備
建立索引及對映
建立價格、顏色、品牌、售賣日期欄位
PUT /tvsPUT /tvs/_mapping
{
"properties": {
"price": {
"type": "long"
},
"color": {
"type": "keyword"
},
"brand": {
"type": "keyword"
},
"sold_date": {
"type": "date"
}
}
}插入資料
POST /tvs/_bulk
{"index":{}}
{"price":1000,"color":"紅色","brand":"長虹","sold_date":"2019-10-28"}
{"index":{}}
{"price":2000,"color":"紅色","brand":"長虹","sold_date":"2019-11-05"}
{"index":{}}
{"price":3000,"color":"綠色","brand":"小米","sold_date":"2019-05-18"}
{"index":{}}
{"price":1500,"color":"藍色","brand":"TCL","sold_date":"2019-07-02"}
{"index":{}}
{"price":1200,"color":"綠色","brand":"TCL","sold_date":"2019-08-19"}
{"index":{}}
{"price":2000,"color":"紅色","brand":"長虹","sold_date":"2019-11-05"}
{"index":{}}
{"price":8000,"color":"紅色","brand":"三星","sold_date":"2020-01-01"}
{"index":{}}
{"price":2500,"color":"藍色","brand":"小米","sold_date":"2020-02-12"}二、 按照顏色分組，計算每個顏色賣出的個數
ES語句
GET /tvs/_search
{
"size": 0,
"query": {
"match_all": {}
},
"aggs": {
"group_by_color": {
"terms": {
"field": "color"
}
}
}
}返回
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_color" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "紅色",
"doc_count" : 4
},
{
"key" : "綠色",
"doc_count" : 2
},
{
"key" : "藍色",
"doc_count" : 2
}
]
}
}
}Java程式碼
//按照顏色分組，計算每個顏色賣出的個數
@Test
public void testAggs() throws IOException {
//1 構建請求
SearchRequest searchRequest=new SearchRequest("tvs");
//請求體
SearchSourceBuilder searchSourceBuilder=new SearchSourceBuilder();
searchSourceBuilder.size(0);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
TermsAggregationBuilder termsAggregationBuilder = AggregationBuilders.terms("group_by_color").field("color");
searchSourceBuilder.aggregation(termsAggregationBuilder);
//請求體放入請求頭
searchRequest.source(searchSourceBuilder);
//2 執行
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
Aggregations aggregations = searchResponse.getAggregations();
Terms group_by_color = aggregations.get("group_by_color");
List<? extends Terms.Bucket> buckets = group_by_color.getBuckets();
for (Terms.Bucket bucket : buckets) {
String key = bucket.getKeyAsString();
System.out.println("key:"+key);
long docCount = bucket.getDocCount();
System.out.println("docCount:"+docCount);
System.out.println("=================================");
}
}結果
三、按照顏色分組，計算每個顏色賣出的個數，每個顏色賣出的平均價格
ES語句
GET /tvs/_search
{
"size": 0,
"query": {
"match_all": {}
},
"aggs": {
"group_by_color": {
"terms": {
"field": "color"
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
}
}
}
}
}返回結果
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_color" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "紅色",
"doc_count" : 4,
"avg_price" : {
"value" : 3250.0
}
},
{
"key" : "綠色",
"doc_count" : 2,
"avg_price" : {
"value" : 2100.0
}
},
{
"key" : "藍色",
"doc_count" : 2,
"avg_price" : {
"value" : 2000.0
}
}
]
}
}
}Java程式碼
// 按照顏色分組，計算每個顏色賣出的個數，每個顏色賣出的平均價格
@Test
public void testAggsAndAvg() throws IOException {
//1 構建請求
SearchRequest searchRequest=new SearchRequest("tvs");
//請求體
SearchSourceBuilder searchSourceBuilder=new SearchSourceBuilder();
searchSourceBuilder.size(0);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
TermsAggregationBuilder termsAggregationBuilder = AggregationBuilders.terms("group_by_color").field("color");
//terms聚合下填充一個子聚合
AvgAggregationBuilder avgAggregationBuilder = AggregationBuilders.avg("avg_price").field("price");
termsAggregationBuilder.subAggregation(avgAggregationBuilder);
searchSourceBuilder.aggregation(termsAggregationBuilder);
//請求體放入請求頭
searchRequest.source(searchSourceBuilder);
//2 執行
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
Aggregations aggregations = searchResponse.getAggregations();
Terms group_by_color = aggregations.get("group_by_color");
List<? extends Terms.Bucket> buckets = group_by_color.getBuckets();
for (Terms.Bucket bucket : buckets) {
String key = bucket.getKeyAsString();
System.out.println("key:"+key);
long docCount = bucket.getDocCount();
System.out.println("docCount:"+docCount);
Aggregations aggregations1 = bucket.getAggregations();
Avg avg_price = aggregations1.get("avg_price");
double value = avg_price.getValue();
System.out.println("value:"+value);
System.out.println("=================================");
}
}返回結果
四、按照顏色分組，計算每個顏色賣出的個數，以及每個顏色賣出的平均值、最大值、最小值、總和
ES語句
GET /tvs/_search
{
"size": 0,
"aggs": {
"group_by_color": {
"terms": {
"field": "color"
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
},
"min_price": {
"min": {
"field": "price"
}
},
"max_price": {
"max": {
"field": "price"
}
},
"sum_price": {
"sum": {
"field": "price"
}
}
}
}
}
}返回結果
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"group_by_color" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "紅色",
"doc_count" : 4,
"max_price" : {
"value" : 8000.0
},
"min_price" : {
"value" : 1000.0
},
"avg_price" : {
"value" : 3250.0
},
"sum_price" : {
"value" : 13000.0
}
},
{
"key" : "綠色",
"doc_count" : 2,
"max_price" : {
"value" : 3000.0
},
"min_price" : {
"value" : 1200.0
},
"avg_price" : {
"value" : 2100.0
},
"sum_price" : {
"value" : 4200.0
}
},
{
"key" : "藍色",
"doc_count" : 2,
"max_price" : {
"value" : 2500.0
},
"min_price" : {
"value" : 1500.0
},
"avg_price" : {
"value" : 2000.0
},
"sum_price" : {
"value" : 4000.0
}
}
]
}
}
}Java程式碼
// 按照顏色分組，計算每個顏色賣出的個數，以及每個顏色賣出的平均值、最大值、最小值、總和。
@Test
public void testAggsAndMore() throws IOException {
//1 構建請求
SearchRequest searchRequest=new SearchRequest("tvs");
//請求體
SearchSourceBuilder searchSourceBuilder=new SearchSourceBuilder();
searchSourceBuilder.size(0);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
TermsAggregationBuilder termsAggregationBuilder = AggregationBuilders.terms("group_by_color").field("color");
//termsAggregationBuilder裡放入多個子聚合
AvgAggregationBuilder avgAggregationBuilder = AggregationBuilders.avg("avg_price").field("price");
MinAggregationBuilder minAggregationBuilder = AggregationBuilders.min("min_price").field("price");
MaxAggregationBuilder maxAggregationBuilder = AggregationBuilders.max("max_price").field("price");
SumAggregationBuilder sumAggregationBuilder = AggregationBuilders.sum("sum_price").field("price");
termsAggregationBuilder.subAggregation(avgAggregationBuilder);
termsAggregationBuilder.subAggregation(minAggregationBuilder);
termsAggregationBuilder.subAggregation(maxAggregationBuilder);
termsAggregationBuilder.subAggregation(sumAggregationBuilder);
searchSourceBuilder.aggregation(termsAggregationBuilder);
//請求體放入請求頭
searchRequest.source(searchSourceBuilder);
//2 執行
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
Aggregations aggregations = searchResponse.getAggregations();
Terms group_by_color = aggregations.get("group_by_color");
List<? extends Terms.Bucket> buckets = group_by_color.getBuckets();
for (Terms.Bucket bucket : buckets) {
String key = bucket.getKeyAsString();
System.out.println("key:"+key);
long docCount = bucket.getDocCount();
System.out.println("docCount:"+docCount);
Aggregations aggregations1 = bucket.getAggregations();
Max max_price = aggregations1.get("max_price");
double maxPriceValue = max_price.getValue();
System.out.println("maxPriceValue:"+maxPriceValue);
Min min_price = aggregations1.get("min_price");
double minPriceValue = min_price.getValue();
System.out.println("minPriceValue:"+minPriceValue);
Avg avg_price = aggregations1.get("avg_price");
double avgPriceValue = avg_price.getValue();
System.out.println("avgPriceValue:"+avgPriceValue);
Sum sum_price = aggregations1.get("sum_price");
double sumPriceValue = sum_price.getValue();
System.out.println("sumPriceValue:"+sumPriceValue);
System.out.println("=================================");
}
}返回結果
五、按照售價每2000價格劃分範圍，算出每個區間的銷售總額
ES語句
GET /tvs/_search
{
"size": 0,
"aggs": {
"by_histogram": {
"histogram": {
"field": "price",
"interval": 2000
},
"aggs": {
"income": {
"sum": {
"field": "price"
}
}
}
}
}
}返回結果
檢視程式碼
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"by_histogram" : {
"buckets" : [
{
"key" : 0.0,
"doc_count" : 3,
"income" : {
"value" : 3700.0
}
},
{
"key" : 2000.0,
"doc_count" : 4,
"income" : {
"value" : 9500.0
}
},
{
"key" : 4000.0,
"doc_count" : 0,
"income" : {
"value" : 0.0
}
},
{
"key" : 6000.0,
"doc_count" : 0,
"income" : {
"value" : 0.0
}
},
{
"key" : 8000.0,
"doc_count" : 1,
"income" : {
"value" : 8000.0
}
}
]
}
}
}Java程式碼
// 按照售價每2000價格劃分範圍，算出每個區間的銷售總額 histogram
@Test
public void testAggsAndHistogram() throws IOException {
//1 構建請求
SearchRequest searchRequest=new SearchRequest("tvs");
//請求體
SearchSourceBuilder searchSourceBuilder=new SearchSourceBuilder();
searchSourceBuilder.size(0);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
HistogramAggregationBuilder histogramAggregationBuilder =
AggregationBuilders.histogram("by_histogram").field("price").interval(2000);
SumAggregationBuilder sumAggregationBuilder = AggregationBuilders.sum("income").field("price");
histogramAggregationBuilder.subAggregation(sumAggregationBuilder);
searchSourceBuilder.aggregation(histogramAggregationBuilder);
//請求體放入請求頭
searchRequest.source(searchSourceBuilder);
//2 執行
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
Aggregations aggregations = searchResponse.getAggregations();
Histogram group_by_color = aggregations.get("by_histogram");
List<? extends Histogram.Bucket> buckets = group_by_color.getBuckets();
for (Histogram.Bucket bucket : buckets) {
String keyAsString = bucket.getKeyAsString();
System.out.println("keyAsString:"+keyAsString);
long docCount = bucket.getDocCount();
System.out.println("docCount:"+docCount);
Aggregations aggregations1 = bucket.getAggregations();
Sum income = aggregations1.get("income");
double value = income.getValue();
System.out.println("value:"+value);
System.out.println("=================================");
}
}返回結果
六、計算每個季度的銷售總額
ES語句
GET /tvs/_search
{
"size": 0,
"aggs": {
"sales": {
"date_histogram": {
"field": "sold_date",
"interval": "quarter",
"format": "yyyy-MM-dd",
"min_doc_count": 0,
"extended_bounds": {
"min": "2019-01-01",
"max": "2020-12-31"
}
},
"aggs": {
"income": {
"sum": {
"field": "price"
}
}
}
}
}
}返回結果
檢視程式碼
#! Deprecation: [interval] on [date_histogram] is deprecated, use [fixed_interval] or [calendar_interval] in the future.
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"sales" : {
"buckets" : [
{
"key_as_string" : "2019-01-01",
"key" : 1546300800000,
"doc_count" : 0,
"income" : {
"value" : 0.0
}
},
{
"key_as_string" : "2019-04-01",
"key" : 1554076800000,
"doc_count" : 1,
"income" : {
"value" : 3000.0
}
},
{
"key_as_string" : "2019-07-01",
"key" : 1561939200000,
"doc_count" : 2,
"income" : {
"value" : 2700.0
}
},
{
"key_as_string" : "2019-10-01",
"key" : 1569888000000,
"doc_count" : 3,
"income" : {
"value" : 5000.0
}
},
{
"key_as_string" : "2020-01-01",
"key" : 1577836800000,
"doc_count" : 2,
"income" : {
"value" : 10500.0
}
},
{
"key_as_string" : "2020-04-01",
"key" : 1585699200000,
"doc_count" : 0,
"income" : {
"value" : 0.0
}
},
{
"key_as_string" : "2020-07-01",
"key" : 1593561600000,
"doc_count" : 0,
"income" : {
"value" : 0.0
}
},
{
"key_as_string" : "2020-10-01",
"key" : 1601510400000,
"doc_count" : 0,
"income" : {
"value" : 0.0
}
}
]
}
}
}Java程式碼
// 計算每個季度的銷售總額
@Test
public void testAggsAndDateHistogram() throws IOException {
//1 構建請求
SearchRequest searchRequest=new SearchRequest("tvs");
//請求體
SearchSourceBuilder searchSourceBuilder=new SearchSourceBuilder();
searchSourceBuilder.size(0);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
DateHistogramAggregationBuilder dateHistogramAggregationBuilder =
AggregationBuilders.dateHistogram("date_histogram")
.field("sold_date")
.calendarInterval(DateHistogramInterval.QUARTER)
.format("yyyy-MM-dd")
.minDocCount(0)
.extendedBounds(new ExtendedBounds("2019-01-01", "2020-12-31"));
SumAggregationBuilder sumAggregationBuilder =
AggregationBuilders.sum("income").field("price");
dateHistogramAggregationBuilder.subAggregation(sumAggregationBuilder);
searchSourceBuilder.aggregation(dateHistogramAggregationBuilder);
//請求體放入請求頭
searchRequest.source(searchSourceBuilder);
//2 執行
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
Aggregations aggregations = searchResponse.getAggregations();
ParsedDateHistogram date_histogram = aggregations.get("date_histogram");
List<? extends Histogram.Bucket> buckets = date_histogram.getBuckets();
for (Histogram.Bucket bucket : buckets) {
String keyAsString = bucket.getKeyAsString();
System.out.println("keyAsString:"+keyAsString);
long docCount = bucket.getDocCount();
System.out.println("docCount:"+docCount);
Aggregations aggregations1 = bucket.getAggregations();
Sum income = aggregations1.get("income");
double value = income.getValue();
System.out.println("value:"+value);
System.out.println("====================");
}
}返回結果
本文來自部落格園，作者：|舊市拾荒|，轉載請註明原文連結：https://www.cnblogs.com/xiaoyh/p/16268683.html