I want to upload table [Excel file] on windows azure Mobile services without coding. Can server side scripting is use for this? Any other option to upload it on Azure Mobile Service Data?
No, there's no automatic way to do that. You will need to read your table from the excel file and upload the rows to the server. That should be fairly easy to implement - save your file as a comma-separated value list (or tab-separated value list, which should make parsing easier). In a program which uses the mobile service SDK you'd read the lines from the CSV (or TSV) file, convert it to the appropriate structure (either directly to JSON via the JObject type or a typed class) and call the InsertAsync method in the client to insert the data to the server.
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Our organization is migrating our routine work onto Azure Cloud platform. One of my works is using Python to read many pdf files and convert all the text/unstructured data into tables, e.g.
first column shows the file name and second column saves all the text data etc.
Just wondering is there a service in Azure platform that can achieve this automatically? I am new user to Azure, so not quite familiar with this. Thanks heaps if any help.
I would recommend looking at Azure Form Recognizer. You can train it to recognize tables and extract data from PDF files.
I am looking to import data form a publicly available Excel sheet into ADF. I have set up the dataset using an HTTP linked service (see first screenshot), with AutoResolveIntegrationRuntime. However, when I attempt to preview the data, I get an error suggestion that the source file is not in the correct format (second screenshot).
I'm wondering if I may have something set incorrectly in my configuration?
.xls format is not supported while using HTTP.
Since, the API downloads file you can't preview data. You can load file to blob or Azure Datalake Storage using copy activity and then on top of that file have a dataset to preview.
The workaround is to save your .xlsx file as a .csv file because Azure Data Factory does not support reading .xlsx files explicitly for HTTP connectors.
Furthermore, there is no need to convert the.xlsx file to.csv if you only want to copy it; simply select the Binary Copy option.
Here, is a similar discussion where the MS-FTE has confirmed with Product Team that's its not supported yet for HTTP Connector.
Please submit a proposal in the QnA thread to allow this functionality in future versions, which will be actively monitored by the data factory product team and evaluated for adoption.
Please check the issue at QnA Thread- Here.
I want to create a list from an excel sheet I am uploading to SharePoint using Azure Logic Apps. Now I want to use this app to update a list on SharePoint using the same excel file. It is getting executed but gives absurd values in the list. Please help me to know how can I make this work.
This is because you just pass the file content not the items, the logic app won't do data processing, you need design you flow to process the data then create item one by one.
Below is my test flow, I get the csv file from SharePoint then I use Plumsail Parse CSV action to get the items. If you are processing other excel file you could use excel connector to get rows.
Here is my test result.
Does anyone have guidance and/or example code (which would be awesome) on how I would go about the following?
With a Web application using C# / ASP.NET MVC and hosted on Azure:
Allow a user to upload an Excel Workbook (multiple worksheets) via a web page UI
Populate a Dataset by reading in the worksheets so I can then process the data
Couple of things I'm unclear on:
I've read that Azure doesn't have ACEOLEDB, which is what Excel 2007+ requires, and I'd have to use OPEN XML SDK. Is this true? Is this the only way?
Is it possible to read the file into memory and not actually save it to Azure storage?
I DO NOT need to modify the uploaded spreadsheet. Only read the data in and then throw the spreadsheet away.
Well that's many questions in one post, let me see if we can tackle them one by one
With a Web application using C# / ASP.NET MVC and hosted on Azure:
1.Allow a user to upload an Excel Workbook (multiple worksheets) via a web page UI
2.Populate a Dataset by reading in the worksheets so I can then process the data
Couple of things I'm unclear on:
1.I've read that Azure doesn't have ACEOLEDB, which is what Excel 2007+ requires, and I'd have to use OPEN XML SDK. Is this true? Is
this the only way?
2.Is it possible to read the file into memory and not actually save it to Azure storage?
1/2. You can allow a user to upload the excel workbook to some /temp location and once you have read you can choose to do the cleanup, you can also write a script which can do the cleanup of the files which couldn't get deleted from /temp for whatever reasons.
Alternatively if you want to keep the files, you should store them in Azure Stoarge, and fetch/read when you need to.
check out this thread read excelsheet in azure uploaded as a blob
By default when you upload a file it is wrote into local disk and one later chooses to save the files to azure storage or whatever places.
Reading the excel - you can use any of the nugget packages given here http://nugetmusthaves.com/Tag/Excel and read the excel file, I prefer Gembox and NPOI
http://www.aspdotnet-suresh.com/2014/12/how-to-upload-files-in-asp-net-mvc-razor.html
What would be the best way to use IFilter to extract textual content from pdf/word/whatever in an Azure solution?
I've seen examples of IFilter that use a stream, but what should the content of the stream be?
Should it contain some sort of OLE headers and what not?
Sending the raw file content as a stream to IFilter doesnt seem to work.
Or would it be better to save the files to local file storage and let the IFilter read them from that location?
using ifilter in azure will be tricky because several of the ifilters that are common on a desktop aren't available in an azure web/worker role.
You could create a durable VM in azure and install the missing ifilters.
However, if you're going to build your lucene index via a webupload you could just process the files into text as they are uploaded, and then index the text, and save the file off separately. Add a field to your index that lets you get back to the original source document.
Might be an easier way, but that's how I solved the same issue.