Azure databricks 还原备份的操作

lbl2512024-03-29 11:32

起因：databricks 面临从HK迁移到国内的情况，目前只是迁移单个库就好，不需要全迁移，问了下azure的技术支持，把数据通过azure客户端azure copy 到指定源--》目标目录就可

这一块参考：

bash 复制代码

 https://docs.microsoft.com/zh-cn/azure/storage/common/storage-use-azcopy-blobs-copy

那拷贝过来后如何读取在storage目录中的数据呢？主要用的是python脚本来读取

bash 复制代码

#1、先要做好集群与storage的验证这一块没有搞好就需要重新来
# 目标表的databases

databaseName_target = "ods_xxx_xxx"

# Create tables including both of partition and non-partition

sqlQueryCreateExternalTable = "CREATE EXTERNAL TABLE IF NOT EXISTS {0}.{1} USING {2} LOCATION '{3}'"
sqlQueryRecoverPartitions = "ALTER TABLE {0}.{1} RECOVER PARTITIONS"
path ="/demo/warehouse/库名/"

for row in tableNames:
    try:
        flag = 0
        partitionName = ""
        tableBaseDirectory = spark.createDataFrame(dbutils.fs.ls((row["path"].replace('dbfs:', '')))).collect()

        for rowDirectory in tableBaseDirectory:
#            print(rowDirectory)
            if rowDirectory["size"] != 0:
                flag = -1
            else:
                partitionName = rowDirectory["name"].split('=')[0]
                
        if flag == -1:
            spark.sql(sqlQueryCreateExternalTable.format(databaseName_target, row["name"], dataSource, row["path"]))
            print("INFO: {0} completed.".format(sqlQueryCreateExternalTable.format(databaseName_target, row["name"], dataSource, row["path"])))
        else:
            spark.sql(sqlQueryCreateExternalTable.format(databaseName_target, row["name"], dataSource, row["path"]))
            print("WARN: Table {0}.{1} has PARTITIONED BY {2}.".format(databaseName_target, row["name"], partitionName))
            spark.sql(sqlQueryRecoverPartitions.format(databaseName_target, row["name"]))
            print("INFO: Table {0}.{1} has been RECOVER PARTITIONED BY {2} completed.".format(databaseName_target, row["name"], partitionName))
    except Exception as e:
        print(e)
        print("ERROR: Create table {0} failed.".format(row["name"]))