springboot接入influxdb
2023/5/31 1:22:07
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1.添加maven依赖
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> <dependency> <groupId>org.influxdb</groupId> <artifactId>influxdb-java</artifactId> <version>2.14</version> </dependency>
2.spring boot 的application.yaml配置文件中添加influxdb的配置
influxdb: url: http://127.0.0.1:8086 database: influx_db username: influx_db_user password: influx_db_pwd
8086 为influxdb默认的端口
3.influxdb配置应用与service方法编写
import org.influxdb.InfluxDB; import org.influxdb.InfluxDBFactory; import org.influxdb.dto.BatchPoints; import org.influxdb.dto.Point; import org.influxdb.dto.Query; import org.influxdb.dto.QueryResult; import org.springframework.beans.factory.annotation.Value; import org.springframework.stereotype.Service; import javax.annotation.PostConstruct; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; import java.util.concurrent.TimeUnit; @Service public class InfluxDBService { @Value("${influxdb.username}") public String influxdbUserName; @Value("${influxdb.password}") public String influxdbPassword; @Value("${influxdb.url}") public String influxdbUrl; //数据库 @Value("${influxdb.database}") public String influxdbDatabase; @PostConstruct public void initInfluxDb() { this.retentionPolicy = retentionPolicy == null || "".equals(retentionPolicy) ? "autogen" : retentionPolicy; this.influxDB = influxDbBuild(); } //保留策略 private String retentionPolicy; private InfluxDB influxDB; /** * 设置数据保存策略 defalut 策略名 /database 数据库名/ 30d 数据保存时限30天/ 1 副本个数为1/ 结尾DEFAULT * 表示 设为默认的策略 */ public void createRetentionPolicy() { String command = String.format("CREATE RETENTION POLICY \"%s\" ON \"%s\" DURATION %s REPLICATION %s DEFAULT", "defalut", influxdbDatabase, "30d", 1); this.query(command); } /** * 连接时序数据库;获得InfluxDB **/ private InfluxDB influxDbBuild() { if (influxDB == null) { influxDB = InfluxDBFactory.connect(influxdbUrl, influxdbUserName, influxdbPassword); influxDB.setDatabase(influxdbDatabase); } return influxDB; } /** * 插入 * @param measurement 表 * @param tags 标签 * @param fields 字段 */ public void insert(String measurement, Map<String, String> tags, Map<String, Object> fields) { influxDbBuild(); Point.Builder builder = Point.measurement(measurement); builder.time(System.currentTimeMillis(), TimeUnit.MILLISECONDS); builder.tag(tags); builder.fields(fields); influxDB.write(influxdbDatabase, "", builder.build()); } /** * @desc 插入,带时间time * @date 2021/3/27 *@param measurement *@param time *@param tags *@param fields * @return void */ public void insert(String measurement, long time, Map<String, String> tags, Map<String, Object> fields) { influxDbBuild(); Point.Builder builder = Point.measurement(measurement); builder.time(time, TimeUnit.MILLISECONDS); builder.tag(tags); builder.fields(fields); influxDB.write(influxdbDatabase, "", builder.build()); } /** * @desc influxDB开启UDP功能,默认端口:8089,默认数据库:udp,没提供代码传数据库功能接口 * @date 2021/3/13 *@param measurement *@param time *@param tags *@param fields * @return void */ public void insertUDP(String measurement, long time, Map<String, String> tags, Map<String, Object> fields) { influxDbBuild(); Point.Builder builder = Point.measurement(measurement); builder.time(time, TimeUnit.MILLISECONDS); builder.tag(tags); builder.fields(fields); int udpPort = 8089; influxDB.write(udpPort, builder.build()); } /** * 查询 * @param command 查询语句 * @return */ public QueryResult query(String command) { influxDbBuild(); return influxDB.query(new Query(command, influxdbDatabase)); } /** * @desc 查询结果处理 * @date 2021/5/12 *@param queryResult */ public List<Map<String, Object>> queryResultProcess(QueryResult queryResult) { List<Map<String, Object>> mapList = new ArrayList<>(); List<QueryResult.Result> resultList = queryResult.getResults(); //把查询出的结果集转换成对应的实体对象,聚合成list for(QueryResult.Result query : resultList){ List<QueryResult.Series> seriesList = query.getSeries(); if(seriesList != null && seriesList.size() != 0) { for(QueryResult.Series series : seriesList){ List<String> columns = series.getColumns(); String[] keys = columns.toArray(new String[columns.size()]); List<List<Object>> values = series.getValues(); if(values != null && values.size() != 0) { for(List<Object> value : values){ Map<String, Object> map = new HashMap(keys.length); for (int i = 0; i < keys.length; i++) { map.put(keys[i], value.get(i)); } mapList.add(map); } } } } } return mapList; } /** * @desc InfluxDB 查询 count总条数 * @date 2021/4/8 */ public long countResultProcess(QueryResult queryResult) { long count = 0; List<Map<String, Object>> list = queryResultProcess(queryResult); if(list != null && list.size() != 0) { Map<String, Object> map = list.get(0); double num = (Double)map.get("count"); count = new Double(num).longValue(); } return count; } /** * 查询 * @param dbName 创建数据库 * @return */ public void createDB(String dbName) { influxDbBuild(); influxDB.createDatabase(dbName); } /** * 批量写入测点 * * @param batchPoints */ public void batchInsert(BatchPoints batchPoints) { influxDbBuild(); influxDB.write(batchPoints); } /** * 批量写入数据 * * @param database 数据库 * @param retentionPolicy 保存策略 * @param consistency 一致性 * @param records 要保存的数据(调用BatchPoints.lineProtocol()可得到一条record) */ public void batchInsert(final String database, final String retentionPolicy, final InfluxDB.ConsistencyLevel consistency, final List<String> records) { influxDbBuild(); influxDB.write(database, retentionPolicy, consistency, records); } /** * @desc 批量写入数据 * @date 2021/3/19 *@param consistency *@param records */ public void batchInsert(final InfluxDB.ConsistencyLevel consistency, final List<String> records) { influxDbBuild(); influxDB.write(influxdbDatabase, "", consistency, records); } }
4.进行单元测试验证
@SpringBootTest public class InfluxDbTest { @Autowired private InfluxDBService influxDBService; @Test void contextLoads() { } @Test public void testSave(){ String measurement = "host_cpu_usage_total"; Map<String,String> tags = new HashMap<>(); tags.put("host_name","host2"); tags.put("cpu_core","core0"); Map<String, Object> fields = new HashMap<>(); fields.put("cpu_usage",0.22); fields.put("cpu_idle",0.56); influxDBService.insert(measurement, tags, fields); } }
influxdb 在执行新增测试用例的时候,如果influxdb的数据库中对应的表不存在,会自动创建数据库表
5.查询示例
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