Hi I have csv file in object storage in Oracle cloud. I want to store this data in the external table which is outside the cloud.can anybody guide me on the same?
How can I read the data from cloud and store in table? I am using Oracle gen2 cloud.
Dbms_cloud is the solution for the above issue.
Related
I am quite new to databricks and looking for a smart way to export a data table from databricks gold scheme to an azure sql database.
I am using databricks as a part of azure resource group, however I do not find data from databricks in any of the storage accounts that are within the same resource group. Does it mean that is is physically stored at en implicit databricks storage account/data lake?
Thanks in advance :-)
The tables you see in Databricks could be have the data stored within that Databricks Workspace file system (DBFS) or somewhere external (e.g. Data Lake, which could be in a different Azure Resource Group) - see here: Databricks databases and tables
For writing data from Databricks to Azure SQL, I would suggest the Apache Spark connector for SQL.
We have a requirement to move data from oracle Cloud storage to Azure Cloud storage.
The requirement is basically to move data from an Oracle ADW database (hosted on Oracle cloud) to Snowflake database (hosted on Azure).
Since the data volume in tables is huge (some with 60mil+ records) we do not wish to use any ETL tool and instead want to setup a pipeline as below.
Oracle ADW database -> Store data in Oracle storage --> Move data to Azure Cloud storage -> Load into Snowflake using snowpipe or similar snowflake utilities.
How should I go about this implementation?
Also share your views on whether we can use Oracle fastconnect and Azure ExpressRoute to directly pull data from Oracle Cloud onto snowflake (or into Azure storage)
I am looking for the same thing with the simplest method from Oracle (on prem but could be cloud), into Snowflake. Looks like data must be exporeted or dropped to external tables, shifted to Azure Blob storage (like AWS S3), then pushed into Snowflake using COPY INTO - basically copying on disk external tables. This is what Snowpipe does:
"Snowpipe copies the files into a queue, from which they are loaded into the target table in a continuous, serverless fashion based on parameters defined in a specified pipe object. The following table indicates the cloud storage service support for automated Snowpipe from Snowflake accounts hosted on each cloud platform:"
It's been a while since I have worked with this. The other option is GoldenGate, which was not expensive the last time I looked into it:
https://www.snowflake.com/blog/continuous-data-replication-into-snowflake-with-oracle-goldengate/
Easy, simple, fast. Anyone have any better ideas would be appreciated.
I have incoming blobs in azure storage account for every day-hour, now I want to modulate the structure of the JSON inside the blobs and injest them into azure data lake.
I am using azure data factory and databricks.
Can Someone let me know how to proceed with it? I have mounted blob to databricks but now how to create a new structure and then do the mapping?
I need to setup a data pipeline from some source databases like Oracle, MySQL and load the data to BigQuery.
How can I use google-cloud-dataflow to read data from a database(jdbc connection) and write to BigQuery tables using Python.
Also, I have some hive tables in an on-premise Hadoop cluster, how do I transfer this data to BigQuery.
I couldn't find the right documentation or examples to achieve this.
Can you please point me in the right direction.
I applied a solution in my project to provide such thing, you need to follow these steps:
Load data from Google Cloud SQL to Google Cloud storage in CSV by following this link.
Load the CSV data from Google cloud storage directly into BigQuery by following this link.
Is there a way to output U-SQL results directly to a SQL DB such as Azure SQL DB? Couldn't find much about that.
Thanks!
U-SQL only currently outputs to files or internal tables (ie tables within ADLA databases), but you have a couple of options. Azure SQL Database has recently gained the ability to load files from Azure Blob Storage using either BULK INSERT or OPENROWSET, so you could try that. This article shows the syntax and gives a reminder that:
Azure Blob storage containers with public blobs or public containers
access permissions are not currently supported.
wasb://<BlobContainerName>#<StorageAccountName>.blob.core.windows.net/yourFolder/yourFile.txt
BULK INSERT and OPENROWSET with Azure Blob Storage is shown here:
https://blogs.msdn.microsoft.com/sqlserverstorageengine/2017/02/23/loading-files-from-azure-blob-storage-into-azure-sql-database/
You could also use Azure Data Factory (ADF). Its Copy Activity could load the data from Azure Data Lake Storage (ADLS) to an Azure SQL Database in two steps:
execute U-SQL script which creates output files in ADLS (internal tables are not currently supported as a source in ADF)
move the data from ADLS to Azure SQL Database
As a final option, if your data is likely to get into larger volumes (ie Terabytes (TB) then you could use Azure SQL Data Warehouse which supports Polybase. Polybase now supports both Azure Blob Storage and ADLS as a source.
Perhaps if you can tell us a bit more about your process we can refine which of these options is most suitable for you.