BigQuery 커넥터를 사용하여 BigQuery에 대한 프로그래매틱 읽기 및 쓰기 액세스 권한을 사용 설정할 수 있습니다. 이 방법은 BigQuery에 저장된 데이터를 처리하는 최적의 방법입니다. 명령줄 액세스는 공개되지 않습니다.
BigQuery 커넥터는 Spark 및 Hadoop 애플리케이션이 기본 용어를 사용하여 BigQuery의 데이터를 처리하고 BigQuery에 데이터를 쓸 수 있도록 하는 라이브러리입니다.
가격 책정
커넥터 사용시 요금에는 BigQuery 사용 요금이 포함됩니다.
다음 서비스별 요금도 적용될 수 있습니다.
Cloud Storage - 커넥터가 작업 실행 전이나 도중에 데이터를 Cloud Storage 버킷에 다운로드합니다. 작업이 완료되면 데이터가 Cloud Storage에서 삭제됩니다. Cloud Storage 가격에 따라 이 스토리지 요금이 청구됩니다. 초과 요금이 발생하지 않도록 Cloud Storage 계정을 확인하고 불필요한 임시 파일을 삭제하세요.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-08-26(UTC)"],[[["\u003cp\u003eThe BigQuery connector enables Spark and Hadoop applications to programmatically read and write data to BigQuery, without direct command-line access.\u003c/p\u003e\n"],["\u003cp\u003eThe Spark BigQuery Connector, Hive BigQuery Connector, and Hadoop BigQuery Connector are available options for integrating BigQuery with Spark, Hive, and Hadoop, respectively.\u003c/p\u003e\n"],["\u003cp\u003eUtilizing the connector incurs charges for BigQuery usage, Cloud Storage for temporary data, and the BigQuery Storage API for optimized data retrieval.\u003c/p\u003e\n"],["\u003cp\u003eThe connector leverages the BigQuery Storage API to enhance performance when reading data, and it downloads data to a temporary Cloud Storage bucket during job execution.\u003c/p\u003e\n"],["\u003cp\u003eQuick start guides are available for Spark and Java MapReduce to assist users in implementing the BigQuery connector in their workflows.\u003c/p\u003e\n"]]],[],null,["You can use a BigQuery connector to enable programmatic read and write\naccess to [BigQuery](/bigquery). This is an ideal way to process\ndata that is stored in BigQuery. Command-line access is not exposed.\nThe BigQuery connector is a library that enables Spark and Hadoop\napplications to process data from BigQuery and write data to\nBigQuery using its native terminology.\n| The [GoogleCloudDataproc/spark-bigquery-connector](https://github.com/GoogleCloudDataproc/spark-bigquery-connector) is also available for reading data from BigQuery. It takes advantage of the [BigQueryStorage API](/bigquery/docs/reference/storage).\n\nPricing\n\nWhen using the connector, charges include [BigQuery usage fees](/bigquery/pricing).\nThe following service-specific charges may also apply:\n\n- [Cloud Storage](/storage) - the connector downloads data into a Cloud Storage bucket before or during job execution. After the job successfully completes, the data is deleted from Cloud Storage. You are charged for this storage according to [Cloud Storage pricing](/storage/pricing). To avoid excess charges, check your Cloud Storage account and remove unneeded temporary files.\n- [BigQuery Storage API](/bigquery/docs/reference/storage) - to achieve better performance, the connector reads data using the BigQuery Storage API. You are charged for this usage according to [BigQuery Storage API pricing](/bigquery/pricing#storage-api).\n\nAvailable connectors\n\nThe following BigQuery connectors are available for use in\nthe Hadoop ecosystem:\n\n1. The [Spark BigQuery Connector](https://github.com/GoogleCloudDataproc/spark-bigquery-connector) adds a Spark data source, which allows DataFrames to interact directly with BigQuery tables using Spark's `read` and `write` operations.\n2. The [Hive BigQuery Connector](https://github.com/GoogleCloudDataproc/hive-bigquery-connector) adds a Storage Handler, which allows Apache Hive to interact directly with BigQuery tables using HiveQL syntax.\n3. The [Hadoop BigQuery Connector](https://github.com/GoogleCloudDataproc/hadoop-connectors) allows Hadoop mappers and reducers to interact with BigQuery tables using abstracted versions of the [InputFormat](http://hadoop.apache.org/docs/current/api/org/apache/hadoop/mapreduce/InputFormat.html) and [OutputFormat](http://hadoop.apache.org/docs/current/api/org/apache/hadoop/mapreduce/OutputFormat.html) classes.\n\nUse the connectors\n\nFor a quick start using the BigQuery connector, see the following examples:\n\n- [Spark example](/dataproc/docs/tutorials/bigquery-connector-spark-example)\n- [Java MapReduce example](/dataproc/docs/tutorials/bigquery-connector-mapreduce-example)\n- [Connect Dataproc cluster to BigQuery](https://console.cloud.google.com/?walkthrough_id=dataproc--dataproc-bq-spark-connector)\n\nWhat's next\n\n- Learn more about [BigQuery](/bigquery).\n- Follow the [BigQuery example for Spark](/dataproc/docs/tutorials/bigquery-connector-spark-example).\n- Learn more about the [Hive BigQuery Connector](/dataproc/docs/concepts/connectors/hive-bigquery).\n- Follow the [BigQuery example for Java MapReduce](/dataproc/docs/tutorials/bigquery-connector-mapreduce-example)."]]
