SpringCloud3.x集成BigQuery的代碼實現(xiàn)
1.原理
Google BigQuery 是一種高性能、可應(yīng)用于大數(shù)據(jù)分析的公主云數(shù)據(jù)庫服務(wù)。Spring Cloud 提供了完善的工具和核心功能,可以進行泛動分布應(yīng)用構(gòu)建。通過集成 Spring Cloud GCP,應(yīng)用可以便捷地使用 Google 云服務(wù),如 BigQuery。 運行原理如下:
- Spring Cloud GCP 提供對 Google Cloud SDK 和 REST API 的封裝,通過自定義配置簡化了通信流程。
- 通過 BigQueryTemplate,應(yīng)用可以實現(xiàn)數(shù)據(jù)提交、查詢和分析。
- 使用 Spring 框架的常規(guī)構(gòu)件,如信息通道和任務(wù)調(diào)度,應(yīng)用可以進行規(guī)?;瘮?shù)據(jù)處理。
2.應(yīng)用場景
- 大數(shù)據(jù)分析: 選擇 BigQuery 進行大量數(shù)據(jù)的高性能分析,完善商業(yè)準(zhǔn)備和內(nèi)容提報。
- ETL 操作: 連接多種數(shù)據(jù)源,通過規(guī)則創(chuàng)建云數(shù)據(jù)分析的數(shù)據(jù)統(tǒng)一。
- BI 圖表: 使用 BigQuery 提供的高速查詢功能,支持 BI 平臺實現(xiàn)動態(tài)繪圖和數(shù)據(jù)分析。
- 可視化報表: 在進行精簡數(shù)據(jù)計算后,展示對外分析結(jié)果。
3.環(huán)境創(chuàng)建
到 BigQuery 信息中心,為自己創(chuàng)建一個 BigQuery 數(shù)據(jù)集。在資源面板下,點擊您的項目 ID,然后點擊項目下的創(chuàng)建數(shù)據(jù)集。
4.代碼實現(xiàn)
1. 配置環(huán)境
1.1 創(chuàng)建項目
使用 Spring Initializr 創(chuàng)建 Spring Boot 項目,選擇以下依賴:
- Spring Web
- Spring Boot Actuator
- Spring Cloud GCP
1.2 加入依賴
在 pom.xml
中添加以下依賴:
<?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <parent> <artifactId>spring-cloud-gcp</artifactId> <groupId>com.et</groupId> <version>1.0-SNAPSHOT</version> </parent> <modelVersion>4.0.0</modelVersion> <artifactId>spring-cloud-gcp-bigquery-sample</artifactId> <properties> <maven.compiler.source>17</maven.compiler.source> <maven.compiler.target>17</maven.compiler.target> </properties> <dependencies> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency> <dependency> <groupId>com.google.cloud</groupId> <artifactId>spring-cloud-gcp-starter-bigquery</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-thymeleaf</artifactId> </dependency> <!-- Test-related dependencies. --> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <scope>test</scope> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> </dependencies> </project>
2. 配置文件
2.1 application.properties
spring.cloud.gcp.bigquery.dataset-name=test_dataset spring.cloud.gcp.bigquery.project-id=feisty-truth-447013-m7 spring.cloud.gcp.bigquery.credentials.location=file:/path-to-key/keyfile.json
舉例:請將 path-to-key/keyfile.json
替換為你的服務(wù)賬戶私鑰文件路徑。
2.2 IAM 訪問權(quán)限
確保對應(yīng)的服務(wù)賬戶具備以下角色:
BigQuery Data Viewer
BigQuery Job User
使用以下指令加入 IAM 訪問權(quán)限:
gcloud projects add-iam-policy-binding PROJECT_ID \ --member="serviceAccount:YOUR_SERVICE_ACCOUNT_EMAIL" \ --role="roles/bigquery.jobUser"
替換 PROJECT_ID
和 YOUR_SERVICE_ACCOUNT_EMAIL
為你實際的項目 ID 和服務(wù)賬戶郵箱地址。
3. 實現(xiàn)邏輯
3.1 創(chuàng)建接口
將文件上傳至 BigQuery
/* * Copyright 2017-2019 the original author or authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * https://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package com.et; import com.et.BigQuerySampleConfiguration.BigQueryFileGateway; import com.google.cloud.bigquery.*; import com.google.cloud.spring.bigquery.core.BigQueryTemplate; import com.google.cloud.spring.bigquery.core.WriteApiResponse; import org.springframework.beans.factory.annotation.Value; import org.springframework.stereotype.Controller; import org.springframework.ui.ModelMap; import org.springframework.web.bind.annotation.GetMapping; import org.springframework.web.bind.annotation.PostMapping; import org.springframework.web.bind.annotation.RequestParam; import org.springframework.web.multipart.MultipartFile; import org.springframework.web.servlet.ModelAndView; import java.io.ByteArrayInputStream; import java.io.IOException; import java.util.concurrent.CompletableFuture; /** Provides REST endpoint allowing you to load data files to BigQuery using Spring Integration. */ @Controller public class WebController { private final BigQueryFileGateway bigQueryFileGateway; private final BigQueryTemplate bigQueryTemplate; private static final String DATASET_NAME = "datasetName"; @Value("${spring.cloud.gcp.bigquery.datasetName}") private String datasetName; public WebController(BigQueryFileGateway bigQueryFileGateway, BigQueryTemplate bigQueryTemplate) { this.bigQueryFileGateway = bigQueryFileGateway; this.bigQueryTemplate = bigQueryTemplate; } @GetMapping("/") public ModelAndView renderIndex(ModelMap map) { map.put(DATASET_NAME, this.datasetName); return new ModelAndView("index.html", map); } @GetMapping("/write-api-json-upload") public ModelAndView renderUploadJson(ModelMap map) { map.put(DATASET_NAME, this.datasetName); return new ModelAndView("upload-json.html", map); } /** * Handles a file upload using {@link BigQueryTemplate}. * * @param file the JSON file to upload to BigQuery * @param tableName name of the table to load data into * @return ModelAndView of the response the send back to users * @throws IOException if the file is unable to be loaded. */ @PostMapping("/uploadJsonFile") public ModelAndView handleJsonFileUpload( @RequestParam("file") MultipartFile file, @RequestParam("tableName") String tableName, @RequestParam(name = "createTable", required = false) String createDefaultTable) throws IOException { CompletableFuture<WriteApiResponse> writeApiRes; if (createDefaultTable != null && createDefaultTable.equals("createTable")) { // create the default table writeApiRes = this.bigQueryTemplate.writeJsonStream( tableName, file.getInputStream(), getDefaultSchema()); } else { // we are expecting the table to be already existing writeApiRes = this.bigQueryTemplate.writeJsonStream(tableName, file.getInputStream()); } return getWriteApiResponse(writeApiRes, tableName); } private Schema getDefaultSchema() { return Schema.of( Field.of("CompanyName", StandardSQLTypeName.STRING), Field.of("Description", StandardSQLTypeName.STRING), Field.of("SerialNumber", StandardSQLTypeName.NUMERIC), Field.of("Leave", StandardSQLTypeName.NUMERIC), Field.of("EmpName", StandardSQLTypeName.STRING)); } /** * Handles JSON data upload using using {@link BigQueryTemplate}. * * @param jsonRows the String JSON data to upload to BigQuery * @param tableName name of the table to load data into * @return ModelAndView of the response the send back to users */ @PostMapping("/uploadJsonText") public ModelAndView handleJsonTextUpload( @RequestParam("jsonRows") String jsonRows, @RequestParam("tableName") String tableName, @RequestParam(name = "createTable", required = false) String createDefaultTable) { CompletableFuture<WriteApiResponse> writeApiRes; if (createDefaultTable != null && createDefaultTable.equals("createTable")) { // create the default table writeApiRes = this.bigQueryTemplate.writeJsonStream( tableName, new ByteArrayInputStream(jsonRows.getBytes()), getDefaultSchema()); } else { // we are expecting the table to be already existing writeApiRes = this.bigQueryTemplate.writeJsonStream( tableName, new ByteArrayInputStream(jsonRows.getBytes())); } return getWriteApiResponse(writeApiRes, tableName); } private ModelAndView getWriteApiResponse( CompletableFuture<WriteApiResponse> writeApiFuture, String tableName) { String message = null; try { WriteApiResponse apiResponse = writeApiFuture.get(); if (apiResponse.isSuccessful()) { message = "Successfully loaded data to " + tableName; } else if (apiResponse.getErrors() != null && !apiResponse.getErrors().isEmpty()) { message = String.format( "Error occurred while loading the file, printing first error %s. Use WriteApiResponse.getErrors() to get the complete list of errors", apiResponse.getErrors().get(0).getErrorMessage()); } } catch (Exception e) { e.printStackTrace(); message = "Error: " + e.getMessage(); } return new ModelAndView("upload-json.html") .addObject(DATASET_NAME, this.datasetName) .addObject("message", message); } /** * Handles a file upload using {@link BigQueryTemplate}. * * @param file the CSV file to upload to BigQuery * @param tableName name of the table to load data into * @return ModelAndView of the response to send back to users * @throws IOException if the file is unable to be loaded. */ @PostMapping("/uploadFile") public ModelAndView handleFileUpload( @RequestParam("file") MultipartFile file, @RequestParam("tableName") String tableName) throws IOException { CompletableFuture<Job> loadJob = this.bigQueryTemplate.writeDataToTable( tableName, file.getInputStream(), FormatOptions.csv()); return getResponse(loadJob, tableName); } /** * Handles CSV data upload using Spring Integration {@link BigQueryFileGateway}. * * @param csvData the String CSV data to upload to BigQuery * @param tableName name of the table to load data into * @return ModelAndView of the response the send back to users */ @PostMapping("/uploadCsvText") public ModelAndView handleCsvTextUpload( @RequestParam("csvText") String csvData, @RequestParam("tableName") String tableName) { CompletableFuture<Job> loadJob = this.bigQueryFileGateway.writeToBigQueryTable(csvData.getBytes(), tableName); return getResponse(loadJob, tableName); } private ModelAndView getResponse(CompletableFuture<Job> loadJob, String tableName) { String message; try { Job job = loadJob.get(); message = "Successfully loaded data file to " + tableName; } catch (Exception e) { e.printStackTrace(); message = "Error: " + e.getMessage(); } return new ModelAndView("index") .addObject(DATASET_NAME, this.datasetName) .addObject("message", message); } }
以上只是一些關(guān)鍵代碼。
5.測試
在google cloud shell里面運行代碼 運行 $ mvn spring-boot:run 命令。
單擊 Cloud Shell 中的 Web Preview 按鈕以在端口 8080 上預(yù)覽應(yīng)用,并嘗試將一些數(shù)據(jù)加載到數(shù)據(jù)集下的 BigQuery 表中。該應(yīng)用程序接受 CSV 文件上傳或輸入到文本區(qū)域的 CSV 數(shù)據(jù)。如果 BigQuery 數(shù)據(jù)集下尚不存在該表,則會為您創(chuàng)建該表。
查看導(dǎo)入結(jié)果
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