答一凡sir
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!