Spark BigQuery 连接器：BaseEncoding$DecodingException：无法识别的字符：0xa

Question

我正在尝试将 Spark 数据帧从 AWS EMR 集群保存到 BigQuery 表中。我正在使用Spark-bigquery-connector来执行此操作。我已从命令行将 gcloud 凭据服务 json 文件编码为 Base64，然后只需粘贴选项字符串credentials。但这不起作用，并会导致下面的编码错误。我知道我的 json 文件是正确的，因为我在本地运行脚本时使用它。是什么导致了这个问题？

GCLOUD 服务凭证 JSON 文件结构

{
  "type": "service_account",
  "project_id": "<MY_PROJECT_NAME>",
  "private_key_id": "<PRIVATE_KEY_ID>",
  "private_key": "-----BEGIN PRIVATE KEY-----<LONG LIST OF CHARS>-----END PRIVATE KEY-----\n",
  "client_email": "service@project.iam.gserviceaccount.com",
  "client_id": "<CLIENT_ID>",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://oauth2.googleapis.com/token",
  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/<service>%40<project>.iam.gserviceaccount.com"
}

火花代码

df \
        .drop(*cols_to_drop) \
        .write \
        .format("bigquery") \
        .option("temporaryGcsBucket", "emr_spark") \
        .option("credentials", "<LONG_BASE64_STRING>") \
        .option("project", "<MY_PROJECT_NAME>") \
        .option("parentProject", "<MY_PROJECT_NAME>") \
        .option("table", "<MY_PROJECT_NAME>:dataset.table") \
        .mode("overwrite") \
        .save()

错误：

py4j.protocol.Py4JJavaError: An error occurred while calling o137.save.
: java.lang.IllegalArgumentException: com.google.cloud.spark.bigquery.repackaged.com.google.common.io.BaseEncoding$DecodingException: Unrecognized character: 0xa
    at com.google.cloud.spark.bigquery.repackaged.com.google.common.io.BaseEncoding.decode(BaseEncoding.java:219)
    at com.google.cloud.spark.bigquery.repackaged.com.google.api.client.util.Base64.decodeBase64(Base64.java:104)
    at com.google.cloud.spark.bigquery.SparkBigQueryOptions.createCredentials(SparkBigQueryOptions.scala:47)
    at com.google.cloud.spark.bigquery.BigQueryRelationProvider$.createBigQuery(BigQueryRelationProvider.scala:125)
    at com.google.cloud.spark.bigquery.BigQueryRelationProvider$$anonfun$getOrCreateBigQuery$1.apply(BigQueryRelationProvider.scala:107)
    at com.google.cloud.spark.bigquery.BigQueryRelationProvider$$anonfun$getOrCreateBigQuery$1.apply(BigQueryRelationProvider.scala:107)
    at scala.Option.getOrElse(Option.scala:121)
    at com.google.cloud.spark.bigquery.BigQueryRelationProvider.getOrCreateBigQuery(BigQueryRelationProvider.scala:107)
    at com.google.cloud.spark.bigquery.BigQueryRelationProvider.createRelation(BigQueryRelationProvider.scala:79)
    at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
    at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
    at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
    at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
    at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:285)
    at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:748)
Caused by: com.google.cloud.spark.bigquery.repackaged.com.google.common.io.BaseEncoding$DecodingException: Unrecognized character: 0xa
    at com.google.cloud.spark.bigquery.repackaged.com.google.common.io.BaseEncoding$Alphabet.decode(BaseEncoding.java:490)
    at com.google.cloud.spark.bigquery.repackaged.com.google.common.io.BaseEncoding$Base64Encoding.decodeTo(BaseEncoding.java:974)
    at com.google.cloud.spark.bigquery.repackaged.com.google.common.io.BaseEncoding.decodeChecked(BaseEncoding.java:233)
    at com.google.cloud.spark.bigquery.repackaged.com.google.common.io.BaseEncoding.decode(BaseEncoding.java:217)
    ... 39 more

Answer 1

我认为出现此问题是因为连接器需要字符串输入，但 Base64 编码会生成字节对象。因此，简单地对 Base64 编码字节进行 utf-8 解码就解决了我的 DecodingException。

import json
import base64
creds = JSON credentials

# Dump json to str. Encode to utf-8 to get bytes. Encode bytes to Base64 bytes. 
# Decode bytes to get a string
creds64 = base64.b64encode(json.dumps(creds).encode('utf-8')).decode('utf-8')