ClickHouse 入门
简介
ClickHouse 是一个列式数据库，传统的数据库一般是按行存储，而ClickHouse则是按列存储，每一列都有自己的存储空间，并且只存储该列的数值，而不是存储整行的数据。这样做主要有几个好处，压缩率高，查询速度款、支持高并发，ClickHouse在处理大规模数据时具有很高的性能。
优势：
- 数据压缩率高： 由于每列存放相同类型的数据，这些数据在存储时可以采用更高效的压缩算法，从而节省存储空间。
- 查询速度快： 列存储适合于针对某些特定列的查询，因为它只需要加载和处理相关的列数据，比行存储更高效。特别对于大量数据进行聚合运算（如SUM、AVG）的查询，列存储通常更快。
- 支持高并发： 列存储在读取数据时可以仅加载需要的列，提供了更好的并发性能，更适合处理大规模数据查询。
Java 操作ClickHouse
以下使用ClickHouse提供的Java Client V2 客户端操作。
没有使用Java提供的JDBC Driver，主要是考虑可能存在部分特性不支持，后期修改成本较大，同时目前 JDBC Driver 是基于Client V1实现，后期会升级为Client V2，升级的过程可能也会带来一些变动。
配置ClickHouse
基础配置：
@ConfigurationProperties(prefix = "clickhouse")
@Data
@Configuration
public class ClickHouseProperties {
private String url;
private String username;
private String password;
private String database;
}
配置ClickHouse 客户端：
@Configuration
public class ClickHouseConfig {
@Bean
public Client chDirectClient(ClickHouseProperties chProperties) {
return new Client.Builder()
.addEndpoint(chProperties.getUrl())
.setUsername(chProperties.getUsername())
.setPassword(chProperties.getPassword())
// sets the maximum number of connections to the server at a time
// this is important for services handling many concurrent requests to ClickHouse
.setMaxConnections(100)
.setLZ4UncompressedBufferSize(1058576)
.setSocketRcvbuf(500_000)
.setSocketTcpNodelay(true)
.setSocketSndbuf(500_000)
.setClientNetworkBufferSize(500_000)
.allowBinaryReaderToReuseBuffers(true) // using buffer pool for binary reader
// 开启JSON类型的支持，但是目前对于json的实现并不完善，不建议使用
.serverSetting("allow_experimental_json_type", "1")
// allow JSON transcoding as a string
// .serverSetting(ServerSettings.INPUT_FORMAT_BINARY_READ_JSON_AS_STRING, "1")
// .serverSetting(ServerSettings.OUTPUT_FORMAT_BINARY_WRITE_JSON_AS_STRING, "1")
.setDefaultDatabase(chProperties.getDatabase())
.setConnectTimeout(10000)
.setSocketTimeout(10000)
.build();
}
}
增删改查操作
package edu.whu.metadata.dao.clickhouse;
import cn.hutool.core.util.StrUtil;
import com.clickhouse.client.api.Client;
import com.clickhouse.client.api.data_formats.ClickHouseBinaryFormatReader;
import com.clickhouse.client.api.insert.InsertResponse;
import com.clickhouse.client.api.insert.InsertSettings;
import com.clickhouse.client.api.internal.ServerSettings;
import com.clickhouse.client.api.metadata.TableSchema;
import com.clickhouse.client.api.metrics.ServerMetrics;
import com.clickhouse.client.api.query.QueryResponse;
import com.clickhouse.client.api.query.QuerySettings;
import com.clickhouse.data.ClickHouseFormat;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import edu.whu.metadata.entity.TrackData;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.jetbrains.annotations.NotNull;
import org.springframework.data.domain.Page;
import org.springframework.data.domain.PageImpl;
import org.springframework.data.domain.Pageable;
import org.springframework.stereotype.Repository;
import java.io.BufferedReader;
import java.io.ByteArrayInputStream;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.nio.charset.StandardCharsets;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;
import static edu.whu.metadata.entity.TrackData.TABLE_NAME;
@Slf4j
@Repository
public class TrackDataDao {
@Resource
private Client chClient;
InsertSettings insertSettings = new InsertSettings();
/**
流式插入，可以读取csv文件流，写入clickHouse中
*/
public void insertStream(InputStream dataStream) {
try {
try (InsertResponse response = chClient.insert(TABLE_NAME, dataStream, ClickHouseFormat.JSONEachRow,
insertSettings).get(1, TimeUnit.HOURS)) {
log.info("Insert finished: {} rows written", response.getMetrics().getMetric(ServerMetrics.NUM_ROWS_WRITTEN).getLong());
} catch (Exception e) {
log.error("Failed to write JSONEachRow data", e);
throw new RuntimeException(e);
}
} finally {
try {
dataStream.close();
} catch (Exception e) {
log.error("Failed to close data stream", e);
}
}
}
/**
* 插入单条 TrackData 数据
*/
public void insert(TrackData trackData) {
try {
List<TrackData> trackDataList = List.of(trackData);
chClient.insert(TABLE_NAME, trackDataList, insertSettings);
log.info("Inserted TrackData with id {}", trackData.getId());
} catch (Exception e) {
log.error("Failed to insert TrackData", e);
throw new RuntimeException(e);
}
}
public void insertBatch(List<TrackData> trackDataList) {
try {
InsertResponse insertResponse = chClient.insert(TABLE_NAME, trackDataList, insertSettings).get();
log.info("Inserted TrackData with id {}", insertResponse.getMetrics());
} catch (Exception e) {
log.error("Failed to insert TrackData", e);
throw new RuntimeException(e);
}
}
/**
* 根据 id 查询数据
*/
public List<TrackData> findByObjectId(String id) {
List<TrackData> result = new ArrayList<>();
String sql = "SELECT * FROM " + TABLE_NAME + " WHERE object_id = " + id;
QuerySettings querySettings = new QuerySettings();
try (QueryResponse response = chClient.query(sql, querySettings).get()) {
ClickHouseBinaryFormatReader reader = chClient.newBinaryFormatReader(response);
while (reader.hasNext()) {
reader.next();
TrackData trackData = buildTrackData(reader);
result.add(trackData);
}
} catch (Exception e) {
log.error("Failed to query TrackData by id", e);
throw new RuntimeException(e);
}
return result;
}
/**
* 根据地理范围、时间段和 object_id 查询数据，支持分页查询
*/
public Page<TrackData> findByPage(Double minLatitude, Double maxLatitude,
Double minLongitude, Double maxLongitude,
LocalDateTime startTime, LocalDateTime endTime,
String objectId, Pageable pageable) {
List<TrackData> result = new ArrayList<>();
// 构建基础查询语句
StringBuilder sqlBuilder = new StringBuilder("SELECT * FROM " + TABLE_NAME + " WHERE 1=1");
// 根据地理范围添加查询条件
if (minLatitude != null && maxLatitude != null) {
sqlBuilder.append(" AND latitude BETWEEN ").append(minLatitude).append(" AND ").append(maxLatitude);
}
if (minLongitude != null && maxLongitude != null) {
sqlBuilder.append(" AND longitude BETWEEN ").append(minLongitude).append(" AND ").append(maxLongitude);
}
// 根据时间范围添加查询条件 将 LocalDateTime 转换为指定格式的字符串
if (startTime != null && endTime != null) {
DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd'T'HH:mm:ss");
String formattedStartTime = startTime.format(formatter);
String formattedEndTime = endTime.format(formatter);
sqlBuilder.append(" AND timestamp BETWEEN '")
.append(formattedStartTime)
.append("' AND '")
.append(formattedEndTime)
.append("'");
}
// 根据 object_id 添加查询条件
if (objectId != null) {
sqlBuilder.append(" AND object_id = '").append(objectId).append("'");
}
// 添加分页条件
sqlBuilder.append(" LIMIT ").append(pageable.getPageSize()).append(" OFFSET ").append(pageable.getOffset());
String sql = sqlBuilder.toString();
log.info("Generated SQL: {}", sql);
// 执行查询
try (QueryResponse response = chClient.query(sql).get(10, TimeUnit.SECONDS)) {
TableSchema tableSchema = chClient.getTableSchema(TABLE_NAME);
ClickHouseBinaryFormatReader reader = chClient.newBinaryFormatReader(response, tableSchema);
while (reader.hasNext()) {
reader.next();
TrackData trackData = buildTrackData(reader); // 将查询结果转换为 TrackData 对象
result.add(trackData);
}
} catch (Exception e) {
log.error("Failed to query TrackData", e);
throw new RuntimeException(e);
}
long count = 0L;
String countSql = sql.replaceFirst("SELECT \\*", "SELECT COUNT(*)");
countSql = countSql.substring(0, countSql.indexOf("LIMIT"));
log.info("Generated Count SQL: {}", countSql);
try (QueryResponse countResponse = chClient.query(countSql).get(10, TimeUnit.SECONDS)) {
TableSchema countSchema = chClient.getTableSchema(TABLE_NAME);
ClickHouseBinaryFormatReader countReader = chClient.newBinaryFormatReader(countResponse, countSchema);
if (countReader.hasNext()) {
countReader.next();
count = countReader.getLong(1); // 获取 COUNT(*) 的结果
}
} catch (Exception e) {
log.error("Failed to query total count", e);
throw new RuntimeException(e);
}
return new PageImpl<>(result, pageable, count);
}
/**
* 根据 id 删除数据
*/
public void deleteById(Long id) {
String sql = "ALTER TABLE " + TABLE_NAME + " DELETE WHERE id = " + id;
try {
chClient.execute(sql);
log.info("Deleted TrackData with id {}", id);
} catch (Exception e) {
log.error("Failed to delete TrackData", e);
throw new RuntimeException(e);
}
}
@NotNull
private static TrackData buildTrackData(ClickHouseBinaryFormatReader reader) {
TrackData trackData = new TrackData();
trackData.setId(reader.getString("id"));
trackData.setDataType(reader.getString("data_type"));
trackData.setObjectId(reader.getString("object_id"));
trackData.setTimestamp(reader.getLocalDateTime("timestamp"));
trackData.setLatitude(reader.getDouble("latitude"));
trackData.setLongitude(reader.getDouble("longitude"));
trackData.setMetadata(reader.getString("metadata"));
Float speed = StrUtil.isBlankIfStr(reader.getString("speed")) ? null : reader.getFloat("speed");
trackData.setSpeed(speed);
Float heading = StrUtil.isBlankIfStr(reader.getString("heading")) ? null : reader.getFloat("heading");
trackData.setHeading(heading);
Float altitude = StrUtil.isBlankIfStr(reader.getString("altitude")) ? null : reader.getFloat("altitude");
trackData.setAltitude(altitude);
return trackData;
}
}
参考
原文地址：https://blog.csdn.net/qq_38431321/article/details/145249999
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