恢复已删除的表

本文档介绍了���何在 BigQuery 中恢复(或取消删除)已删除的表。您可以在为数据集指定的时间旅行窗口内恢复已删除的表,包括显式删除和基于表过期的隐式删除。您还可以配置时间旅行窗口

如需了解如何恢复已删除的整个数据集或快照,请参阅以下资源:

时间旅行窗口的持续时间可以为 2 到 7 天。时间旅行窗口过后,BigQuery 会提供故障安全期,在该时间段内,已删除的数据会自动额外保留七天。故障安全期过后,您将无法使用任何方法(包括创建支持服务工单)恢复表。

准备工作

确保您拥有必要的 Identity and Access Management (IAM) 权限,以恢复已删除的表。

所需的角色

如需获得恢复已删除表所需的权限,请让您的管理员为您授予项目的 BigQuery User (roles/bigquery.user) IAM 角色。 如需详细了解如何授予角色,请参阅管理对项目、文件夹和组织的访问权限

您也可以通过自定义角色或其他预定义角色来获取所需的权限。

恢复表

从历史数据恢复表时,源表中的标记不会复制到目标表中。

要恢复已删除但仍在时间旅行窗口内的表,您可以使用 @<time> 时间修饰符将该表复制到一个新表。如需复制表,您可以使用 bq 命令行工具或客户端库:

控制台

您无法使用 Google Cloud 控制台恢复删除的表。

bq

  1. In the Google Cloud console, activate Cloud Shell.

    Activate Cloud Shell

    At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

  2. 如需恢复表,请先确定表存在时间的 UNIX 时间戳(以毫秒为单位)。您可以使用 Linux date 命令通过常规时间戳值生成 Unix 时间戳:

    date -d '2023-08-04 16:00:34.456789Z' +%s000
    
  3. 然后,将 bq copy 命令与 @<time> 时间旅行修饰器结合使用来执行表复制操作。

    例如,输入以下命令可将时间为 1418864998000mydataset.mytable 表复制到新表 mydataset.newtable

    bq cp mydataset.mytable@1418864998000 mydataset.newtable
    

    (可选)提供 --location 标志并将其值设置为您的位置

    您还可以指定相对偏移量。以下示例复制一小时前表的版本:

    bq cp mydataset.mytable@-3600000 mydataset.newtable
    

    如需了解详情,请参阅从某个时间点恢复表

Go

试用此示例之前,请按照 BigQuery 快速入门:使用客户端库中的 Go 设置说明进行操作。 如需了解详情,请参阅 BigQuery Go API 参考文档

如需向 BigQuery 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

import (
	"context"
	"fmt"
	"time"

	"cloud.google.com/go/bigquery"
)

// deleteAndUndeleteTable demonstrates how to recover a deleted table by copying it from a point in time
// that predates the deletion event.
func deleteAndUndeleteTable(projectID, datasetID, tableID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydataset"
	// tableID := "mytable"
	ctx := context.Background()
	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %v", err)
	}
	defer client.Close()

	ds := client.Dataset(datasetID)
	if _, err := ds.Table(tableID).Metadata(ctx); err != nil {
		return err
	}
	// Record the current time.  We'll use this as the snapshot time
	// for recovering the table.
	snapTime := time.Now()

	// "Accidentally" delete the table.
	if err := client.Dataset(datasetID).Table(tableID).Delete(ctx); err != nil {
		return err
	}

	// Construct the restore-from tableID using a snapshot decorator.
	snapshotTableID := fmt.Sprintf("%s@%d", tableID, snapTime.UnixNano()/1e6)
	// Choose a new table ID for the recovered table data.
	recoverTableID := fmt.Sprintf("%s_recovered", tableID)

	// Construct and run a copy job.
	copier := ds.Table(recoverTableID).CopierFrom(ds.Table(snapshotTableID))
	copier.WriteDisposition = bigquery.WriteTruncate
	job, err := copier.Run(ctx)
	if err != nil {
		return err
	}
	status, err := job.Wait(ctx)
	if err != nil {
		return err
	}
	if err := status.Err(); err != nil {
		return err
	}

	ds.Table(recoverTableID).Delete(ctx)
	return nil
}

Java

试用此示例之前,请按照 BigQuery 快速入门:使用客户端库中的 Java 设置说明进行操作。 如需了解详情,请参阅 BigQuery Java API 参考文档

如需向 BigQuery 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.CopyJobConfiguration;
import com.google.cloud.bigquery.Job;
import com.google.cloud.bigquery.JobInfo;
import com.google.cloud.bigquery.TableId;

// Sample to undeleting a table
public class UndeleteTable {

  public static void runUndeleteTable() {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    String tableName = "MY_TABLE_TABLE";
    String recoverTableName = "MY_RECOVER_TABLE_TABLE";
    undeleteTable(datasetName, tableName, recoverTableName);
  }

  public static void undeleteTable(String datasetName, String tableName, String recoverTableName) {
    try {
      // Initialize client that will be used to send requests. This client only needs to be created
      // once, and can be reused for multiple requests.
      BigQuery bigquery = BigQueryOptions.getDefaultInstance().getService();

      // "Accidentally" delete the table.
      bigquery.delete(TableId.of(datasetName, tableName));

      // Record the current time.  We'll use this as the snapshot time
      // for recovering the table.
      long snapTime = System.currentTimeMillis();

      // Construct the restore-from tableID using a snapshot decorator.
      String snapshotTableId = String.format("%s@%d", tableName, snapTime);

      // Construct and run a copy job.
      CopyJobConfiguration configuration =
          CopyJobConfiguration.newBuilder(
                  // Choose a new table ID for the recovered table data.
                  TableId.of(datasetName, recoverTableName),
                  TableId.of(datasetName, snapshotTableId))
              .build();

      Job job = bigquery.create(JobInfo.of(configuration));
      job = job.waitFor();
      if (job.isDone() && job.getStatus().getError() == null) {
        System.out.println("Undelete table recovered successfully.");
      } else {
        System.out.println(
            "BigQuery was unable to copy the table due to an error: \n"
                + job.getStatus().getError());
        return;
      }
    } catch (BigQueryException | InterruptedException e) {
      System.out.println("Table not found. \n" + e.toString());
    }
  }
}

Node.js

试用此示例之前,请按照 BigQuery 快速入门:使用客户端库中的 Node.js 设置说明进行操作。 如需了解详情,请参阅 BigQuery Node.js API 参考文档

如需向 BigQuery 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

// Import the Google Cloud client library
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();

async function undeleteTable() {
  // Undeletes "my_table_to_undelete" from "my_dataset".

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const datasetId = "my_dataset";
  // const tableId = "my_table_to_undelete";
  // const recoveredTableId = "my_recovered_table";

  /**
   * TODO(developer): Choose an appropriate snapshot point as epoch milliseconds.
   * For this example, we choose the current time as we're about to delete the
   * table immediately afterwards.
   */
  const snapshotEpoch = Date.now();

  // Delete the table
  await bigquery
    .dataset(datasetId)
    .table(tableId)
    .delete();

  console.log(`Table ${tableId} deleted.`);

  // Construct the restore-from table ID using a snapshot decorator.
  const snapshotTableId = `${tableId}@${snapshotEpoch}`;

  // Construct and run a copy job.
  await bigquery
    .dataset(datasetId)
    .table(snapshotTableId)
    .copy(bigquery.dataset(datasetId).table(recoveredTableId));

  console.log(
    `Copied data from deleted table ${tableId} to ${recoveredTableId}`
  );
}

Python

试用此示例之前,请按照 BigQuery 快速入门:使用客户端库中的 Python 设置说明进行操作。 如需了解详情,请参阅 BigQuery Python API 参考文档

如需向 BigQuery 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为客户端库设置身份验证

import time

from google.cloud import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# TODO(developer): Choose a table to recover.
# table_id = "your-project.your_dataset.your_table"

# TODO(developer): Choose a new table ID for the recovered table data.
# recovered_table_id = "your-project.your_dataset.your_table_recovered"

# TODO(developer): Choose an appropriate snapshot point as epoch
# milliseconds. For this example, we choose the current time as we're about
# to delete the table immediately afterwards.
snapshot_epoch = int(time.time() * 1000)

# ...

# "Accidentally" delete the table.
client.delete_table(table_id)  # Make an API request.

# Construct the restore-from table ID using a snapshot decorator.
snapshot_table_id = "{}@{}".format(table_id, snapshot_epoch)

# Construct and run a copy job.
job = client.copy_table(
    snapshot_table_id,
    recovered_table_id,
    # Must match the source and destination tables location.
    location="US",
)  # Make an API request.

job.result()  # Wait for the job to complete.

print(
    "Copied data from deleted table {} to {}".format(table_id, recovered_table_id)
)

如果您预计可能需要在时间旅行窗口允许的时间后恢复表,请创建该表的表快照。 如需了解详情,请参阅表快照简介

后续步骤