你可以使用以下代码来在Spark/PySpark中进行身份认证并连接到BigQuery： from pyspark.sql import SparkSession # 创建SparkSession spark = SparkSession.builder \ .appName("Example") \ .config("spark.jars", "path/to/bigquery/jars/spark-bigquery-with-dependencies.jar") \ .getOrCreate() # 配置Google服务帐户的密钥文件路径 config = { "spark.driver.extraClassPath": "path/to/google/cloud/sdk/lib/third_party/spark/bigquery/spark-bigquery-latest_2.12.jar", "spark.jars": "path/to/google/cloud/sdk/lib/third_party/spark/bigquery/spark-bigquery-latest_2.12.jar", "spark.executor.extraClassPath": "path/to/google/cloud/sdk/lib/third_party/spark/bigquery/spark-bigquery-latest_2.12.jar", "spark.hadoop.google.cloud.auth.service.account.enable": "true", "spark.hadoop.google.cloud.auth.service.account.json.keyfile": "path/to/ios-app.json" } # 应用配置 spark.conf.setAll(config) # 从BigQuery读取数据 df = spark.read \ .format("bigquery") \ .option("table", "project_id.dataset.table") \ .load() # 显示数据 df.show() 请将代码中的path/to/bigquery/jars/spark-bigquery-with-dependencies.jar和path/to/google/cloud/sdk/lib/third_party/spark/bigquery/spark-bigquery-latest_2.12.jar替换为相应的jar文件的路径。 同时，请将代码中的project_id.dataset.table替换为你要读取数据的BigQuery数据集和表的名称。 这样，你就可以使用Spark/PySpark连接到BigQuery并读取数据了。希望对你有帮助！ ... 展开详请