Is there a way i can transform per minute data logged in azure table storage to hourly ,daily and monthly tables?
I have heard of stream analytics and data lake but don't get how this can be done through above two technologies.
As I know we could do that with Azure Data Factory easily on the azure portal . Please have a try to follow my detail steps.
1.Login the Azure new Portal
2.Add a Data Factory
3.Click [Copy data (preview)] to set properties, we can set Recurring pattern as minute , hourly, daily …as we like
4.Choose the source data store as we like, in the demo I choose azure blob table.
5.Specify new Azure storage connection
6.Select tables from the azure storage which to copy data
7.Apply filter if we want to
8.Select destination data store
9.Table mapping
10.Select Parallel copy settings
11.Get the setting summary
12.We can check that copy action has been done from Data Factory
13.Check from the Azure storage table
Related
I'm new to Azure Data Explorer. Here I need to migrate the data from Azure Table Storage table data into Azure Data Explorer Cluster's Database's Table without using Azure Data Factory.
May be if able to do programatically using .NET, kindly suggest it.
Thanks in advance.
I am looking for way to automatically export data from a Log Analytics table into an Azure SQL database table? Does anyone know how to do this on an automated schedule?
To export log analytics data to Blob storage or ADLS, you can try one of below.
Log Analytics – data export (preview) and example
Archive data from Log Analytics workspace to Azure storage using Logic App
Next ....You can go for Ingest option in ADF.
Next, configure source linked service i.e. Blob Storage or Azure Table storage linked and Sink i.e. SQL DB
Or any relevant source or sink option you want as per the logs stored.
I have been looking for options to migrate data present in my ADLS in one subscription to ADLS in another subscription within Azure. I tried ADF for this purpose and it worked fine.
But the copy speed is too slow in ADF. It copies at a speed of 10-15 KB/sec. Is there some way to increase speed of copy while using ADF?
Yes, there is a way you can migrate data from Azure Data Lake between different subscription: Data Factory.
No matter Data Lake Gen1 or Gen2, Data Factory all support them as the connector. Please ref these tutorials:
Copy data to or from Azure Data Lake Storage Gen1 using Azure Data Factory.
Copy and transform data in Azure Data Lake Storage Gen2 using Azure
Data Factory.
You can create the source and sink dataset in different subscription through linked service:
But this option may cost you some money. You also could ref the Azure Az-copy tutorials: Copy blobs between Azure storage accounts by using AzCopy.
Here is another blog How To Copy Files From One Azure Storage Account To Another:
In this post, Bloger will outline how to copy data from one Azure
Storage Account in one subscription to another Storage Account in
another subscription.
These maybe what you're looking for.
Currently as part of our requirements we are working with the below Azure components
Azure Event Hub
Azure Stream Analytics
Azure Table Storage
Azure Sql DB
Basically with first 3 components, we will be building an Analytics and Reports platform.
Currently as we just started we analyze the data from Azure Table Storage and display it in the analytics dashboard.
Recently we came across a new Azure product Azure Data Lake . Doing some research on microsoft website , we could see we can easily migrate data from Azure Table Storage (with help of Azure Data Factory) to Azure Lake Store. Creating big data pipelines using Azure Data Lake and Azure Data Factory
As we go through the above link, it's mentioned that we need to create an Azure Data Lake Analytics pipeline to process the data.
So what am unclear is the where will be analytics output data will be saved. Do we need to save the analytics output to some DB ? or can we real-time analytics through a Http request ?
We have huge number rows of records in Azure Table Storage that will be moved to Azure Data Lake. For this scenario is it a good option or Can we go an analytics-based solution from Azure Table Storage itself.
Please share your thoughts
You can store your analytics output data on Azure Data Lake Store (a data repository that enables you to store all kinds of data in their raw format without defining schemas.) after processing it through Azure Data lake Analytics (An analytics service that enables you to run jobs on data sets without having to think about clusters.)
As you said "We have huge number rows of records in Azure Table Storage that will be moved to Azure Data Lake.", I think performing analytics on data placed on Azure data lake store is much more efficient because it offers unlimited storage with immediate read/write access to it and scaling the throughput you need for your workloads. It's also offers small writes at low latency for big data sets. So I believe it is better choice then Azure Table storage.
While moving data from Table Storage to SQL Azure, is it possible to obtain only the Delta (The data that hasn't been already moved) using Azure Data Factory?
A more detailed explanation:
There is an Azure Storage Table, which contains some data, which will be updated periodically. And I want to create a Data Factory pipeline which moves this data to an SQL Azure Database. But during each move I only want the newly added data to be written to SQL DB. Is it possible with Azure Data Factory?
See more information on azureTableSourceQuery and copy activity at this link : https://azure.microsoft.com/en-us/documentation/articles/data-factory-azure-table-connector/#azure-table-copy-activity-type-properties.
Also see this link for invoking stored procedure for sql: https://azure.microsoft.com/en-us/documentation/articles/data-factory-azure-sql-connector/#invoking-stored-procedure-for-sql-sink
You can query each time on timestamp to achieve something similar to delta copy, but this is not true delta copy.