How can we create the real-time data pipeline while data resides on Azure Data Lake Storage Gen2, and the analytics has to be done using Elastic Stack.
What can be the integration tool or technique for the completion of this design?
As #Nick.McDermaid mentioned in the comment that you need to reconsider your design. AFAIK there is no such tool available which can integrate Azure Data Lake Gen2 and Elastic Stack for real time analytics.
Alternatively, the better way to implement your requirement is by using the Azure products designed for real time analytics like Azure Stream Analytics, Azure Synapse Analytics, etc. You can also consider Azure Data Factory for data movement and transformation.
You can check out this page to know more about all the analytics products available in Azure. Choose the best which suits your requirement and try to implement using official document examples.
Related
I am pushing events to my Event hub, then this data is being analyzed in Azure Stream Analytics. I'd like to visualize output from stream analytics in Grafana.
What is the easiest approach to achieve this?
Azure Stream Analytics job can natively ingest the data into Azure Data Explorer. https://techcommunity.microsoft.com/t5/azure-data-explorer/azure-data-explorer-is-now-supported-as-output-for-azure-stream/ba-p/2923654
You can then use the Azure Data Explorer plugin in Grafana. https://techcommunity.microsoft.com/t5/azure-data-explorer/azure-data-explorer-is-now-supported-as-output-for-azure-stream/ba-p/2923654
Another option is to use Power BI instead of Grafana. https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-power-bi-dashboard
If I remember correctly, Grafana doesn't store data locally, you need to define a data source on top of one of the compatible storage systems.
Azure Stream Analytics doesn't come with a storage layer either, it's compute only.
So if you want to use ASA and Grafana, you need to output data from ASA to a data source that is supported by Grafana in ingress.
Looking at both lists that leaves only MSSQL via Azure SQL (hopefully it's compatible) as a native option. It's not a bad option for narrow dashboards, or if you intend to store your data in a RDBMS anyway. You can store your entire payload in an NVARCHAR(MAX) if you don't plan to consume the data in SQL.
But being clever, we can actually use the Functions output to write to any other store, or call any API. I'm not sure if Grafana has a direct ingestion API, but Azure Monitor does and it's a supported data source in Grafana.
The other option would be to go through ADX as explained in the other answer.
Not straightforward but doable ;)
Can someone explain the distinct difference between these two products in all major aspects? As far as I am aware from reading the official documents, both could host database systems and provide data cleaning pipeline? Both are on cloud?
Databricks:
Azure Databricks is an Apache Spark-based analytics platform optimized
for the Microsoft Azure cloud services platform. Designed with the
founders of Apache Spark, Databricks is integrated with Azure to
provide one-click setup, streamlined workflows, and an interactive
workspace that enables collaboration between data scientists, data
engineers, and business analysts.
Synapse Analytics:
Azure Synapse is a limitless analytics service that brings together
enterprise data warehousing and Big Data analytics. It gives you the
freedom to query data on your terms, using either serverless on-demand
or provisioned resources—at scale. Azure Synapse brings these two
worlds together with a unified experience to ingest, prepare, manage,
and serve data for immediate BI and machine learning needs
they do overlap to some extent, but they are not the same thing. Databricks is pretty much managed Apache Spark, whereas Synapse Analytics is managed SQL Data Warehouse.
I want to integrate Azure data lake storage with Grafana for visualization of time series data. I need to know what all the tools I can use to make it possible.
I used ADF to extract data from csv files stored in data lake and move to a table in Azure data explorer. After that, I used Azure data explorer plugin in grafana to visualize the same. It worked fine. But I need to know is there any other approach which may be better or cost-effective.
Integrating Grafana with Azure Data Lake is the best option when compared to others because the other options include data movements using ADF and additional cost for Azure SQL Datawarehouse along with the cost of PowerBI.
Reason:
Grafana is a leading open source software designed for visualizing time series analytics. It is an analytics and metrics platform that enables you to query and visualize data and create and share dashboards based on those visualizations. Combining Grafana’s beautiful visualizations with Azure Data Explorer’s snappy ad hoc queries over massive amounts of data, creates impressive usage potential.
The Grafana and Azure Data Explorer teams have created a dedicated plugin which enables you to connect to and visualize data from Azure Data Explorer using its intuitive and powerful Kusto Query Language. In just a few minutes, you can unlock the potential of your data and create your first Grafana dashboard with Azure Data Explorer.
For more details on visualizing data from Azure Data Explorer in Grafana please visit our documentation, “Visualize data from Azure Data Explorer in Grafana”.
Other options:
For Azure Data Lake Gen1:
You can use a mix of services to create visual representations of data stored in Data Lake Storage Gen1.
You can start by using Azure Data Factory to move data from Data Lake Storage Gen1 to Azure SQL Data Warehouse.
After that, you can integrate Power BI with Azure SQL Data Warehouse to create visual representation of the data.
For Azure Data Lake Gen2:
You can use a mix of services to create visual representations of data stored in Data Lake Storage Gen2.
You can start by using Azure Data Factory to move data from Data Lake Storage Gen2 to Azure SQL Data Warehouse.
After that, you can integrate Power BI with Azure SQL Data Warehouse to create visual representation of the data.
Hope this helps.
They just released a new guide. This is for Grafana 5.3
https://learn.microsoft.com/en-us/azure/data-explorer/grafana
you are able to test this by running Grafana in a Docker container (or for real, if you want). I followed the guide, and it is working almost exactly as expected. The only issue I am having is Grafana is concatenating the column name and the data in the column, making reading and formatting tricky.
I am using a Azure Data Lake Store gen1 for storing JSON files. Based on these files i have Notebooks in Azure Databricks for processing them. Now i want to trigger such a Azure Databricks Notebook when a new file is creating in Azure Data Lake Store gen1. I couldnt find any Trigger which could do this. do you know any way?
Currently, this is not yet implemented/Supported by Microsoft. But it is on their Roadmap(I believe).
You can do this in 2 ways,
Azure Functions(through Event Grid)
Logic Apps
Option #1
Currently, Microsoft is building on #1.
You can track the issue here.
As per this
This feature is not a high priority for us right now, but I will note
that the announcement for Azure Event Grid listed Data Lake as one of
the integrations they are building. Once you can subscribe to Data
Lake updates through Event Grid, running an Azure Function would be
trivial (see here for some info).
You can vote your voice to support the event grid (provider) in DataLake.
Option #2
This is also not yet implemented, but you can Upvote your voice here to support this feature
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.