java把数据批量插入iotdb
package com.xlkh.kafka;
import cn.hutool.core.collection.CollectionUtil;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONArray;
import com.google.common.collect.Lists;
import com.google.common.collect.Sets;
import lombok.SneakyThrows;
import lombok.extern.slf4j.Slf4j;
import org.apache.iotdb.rpc.IoTDBConnectionException;
import org.apache.iotdb.rpc.StatementExecutionException;
import org.apache.iotdb.session.pool.SessionPool;
import org.apache.iotdb.tsfile.file.metadata.enums.CompressionType;
import org.apache.iotdb.tsfile.file.metadata.enums.TSDataType;
import org.apache.iotdb.tsfile.file.metadata.enums.TSEncoding;
import org.apache.iotdb.tsfile.write.record.Tablet;
import org.apache.iotdb.tsfile.write.schema.MeasurementSchema;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.*;
import java.util.stream.Collectors;
@Slf4j
@Component("com.xlkh.kafka.DataLoaderKafkaConsumer")
public class DataLoaderKafkaConsumer {
@Autowired
private SessionPool sessionPool;
/**
* 保存已经创建的时间序列
*/
private final static Set<String> STATIC_PATHS = Sets.newConcurrentHashSet();
/**
* fluent_data,批量消费
*/
@KafkaListener(topics = "fluent_data", groupId = "fluent_data_demo", containerFactory = "batchFactory")
@SneakyThrows
public void listenBatchByFluent(List<ConsumerRecord<String, String>> records) {
log.error("从kafka消费fluent数据" + records.size() + "条,当前偏移量:" + records.get(0).offset());
//创建时间序列,如果序列已经存在,不再重新创建
createTimeseriesIfNotExist(records);
log.info("开始把数据放到iotdb-----------------------");
insertIotdbByKafka(records);
}
private void insertIotdbByKafka(List<ConsumerRecord<String, String>> records) throws ParseException, IoTDBConnectionException, StatementExecutionException {
//key为kks的路径,value是时间戳集合
Map<String, List<Long>> timeStampMap = new HashMap<>();
//key为kks路径,value是具体的数据
Map<String, List<Float>> values = new HashMap<>();
//保存kks编码
Set<String> kksSet = new HashSet<>();
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (ConsumerRecord<String, String> record : records) {
String valueData = record.value();
JSONArray jsonArray = JSON.parseArray(valueData);
for (int i = 0; i < jsonArray.size(); i++) {
Map map = JSON.parseObject(String.valueOf(jsonArray.get(i)), Map.class);
JSONArray jsonArray1 = JSON.parseArray(String.valueOf(map.get("msg")));
for (int j = 0; j < jsonArray1.size(); j++) {
Map map1 = JSON.parseObject(String.valueOf(jsonArray1.get(j)), Map.class);
if (map1.containsKey("big_v")){
String kks = map1.get("kks").toString();
Date date = dateFormat.parse(map1.get("time").toString());
Float val = Float.parseFloat(String.valueOf(map1.get("big_v")));
if(!kksSet.contains(kks)){
timeStampMap.put(kks, new ArrayList<>());
values.put(kks, new ArrayList<>());
kksSet.add(kks);
}
timeStampMap.get(kks).add(date.getTime());
values.get(kks).add(val);
}
}
}
}
//遍历批量插入每个设备的数据
for (String kks : kksSet) {
List<Long> longs = timeStampMap.get(kks);
//声明Tablet对象设备属性
List<MeasurementSchema> schemas = new ArrayList<>();
schemas.add(new MeasurementSchema(kks,TSDataType.FLOAT));
Tablet tablet = new Tablet("root.param.demo", schemas, longs.size());
for (int row = 0; row < longs.size(); row++) {
int rowIndex = tablet.rowSize++;
//设备时间戳值
tablet.addTimestamp(rowIndex, longs.get(row));
//设置对应的值
tablet.addValue(schemas.get(0).getMeasurementId(), rowIndex, values.get(kks).get(row));
}
//批量插入数据
sessionPool.insertTablet(tablet);
}
log.info("数据成功插入到iotdb-----------------------"+"插入的数据量大小为:"+records.size());
}
/**
* 创建时间序列,如果序列已经存在,不再重新创建
*
* @param records 批量数据
*/
private void createTimeseriesIfNotExist(List<ConsumerRecord<String, String>> records) {
try {
List<String> data = records.stream().map(ConsumerRecord::value).collect(Collectors.toList());
HashSet<String> paths = Sets.newHashSetWithExpectedSize(250);
for (String msg : data) {
JSONArray jsonArray = JSON.parseArray(msg);
for (int i = 0; i <jsonArray.size() ; i++) {
Map map = JSON.parseObject(String.valueOf(jsonArray.get(i)), Map.class);
JSONArray jsonArray1 = JSON.parseArray(String.valueOf(map.get("msg")));
for (int j = 0; j < jsonArray1.size(); j++){
Map map1 = JSON.parseObject(String.valueOf(jsonArray1.get(j)), Map.class);
String kks = map1.get("kks").toString();
String path = "root.param.demo." + kks;
paths.add(path);
}
}
}
List<String> notExistPaths = Lists.newArrayList();
List<TSDataType> tsDataTypes = Lists.newArrayList();
List<TSEncoding> tsEncodings = Lists.newArrayList();
List<CompressionType> compressionTypes = Lists.newArrayList();
// List<Map<String, String>> propsList = Lists.newArrayList();
for (String path : paths) {
if (!STATIC_PATHS.contains(path)) {
if (sessionPool.checkTimeseriesExists(path)) {
STATIC_PATHS.add(path);
} else {
notExistPaths.add(path);
tsDataTypes.add(TSDataType.FLOAT);
tsEncodings.add(TSEncoding.RLE);
compressionTypes.add(CompressionType.SNAPPY);
}
}
}
if (CollectionUtil.isNotEmpty(notExistPaths)) {
//批量创建时间序列
sessionPool.createMultiTimeseries(notExistPaths, tsDataTypes, tsEncodings, compressionTypes, null, null, null, null);
//缓存时间序列
STATIC_PATHS.addAll(notExistPaths);
}
} catch (IoTDBConnectionException | StatementExecutionException e) {
log.error(e.getMessage(), e);
}
}
}
切记:对于iotdb来说,节点的第一层一直到倒数第二层,都属于设备id,只有最后一层才是你的属性
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