Using Azure Mobile Services and Azure Easy Tables on the back end I want to get filtered data on the client since tables could be quite large but useful rows to specific user with own ID wouldn't be. I tried to use
IMobileServiceTableQuery<Messages> query =
msgTable.Where(c => c.UserId==_myId);
await msgTable.PullAsync("syncmsg"+_myid, query);
but it turns out that PullAsync apply query only on next times but first time it pulls all data. It there any way using Azure Mobile Services pull and store on local storage only filtered on query data?
So, first things first - you should do security filtering on the server, not the client. There are easy ways to adjust the filter on the server for your specifications. See https://github.com/Azure/azure-mobile-apps-node/tree/master/samples for plenty of samples.
As to this issue, you are building the query wrong. The thing you want is:
var query = msgTable.CreateQuery().Where(c => c.UserId == myId);
await msgTable.PullAsync('mysyncquery', query);
Note the CreateQuery() in the middle. Without that, you don't get the base query set up.
Related
I have 1000 records that I need to sync daily from an API. I am currently bulk inserting them into a SQL Database, however I would like to use Dataverse/a Common Data Service database instead.
The Logic App connector seems to do 1 record at a time and the SDK does PUTS and POSTS. How can I either insert 1000 records into the Common Data Service in bulk OR somehow synchronise my SQL DB with the CDS?
As far as I know there is no another way to do that without programming. You can extended your Power Automate Flow with Azure Functions to insert these records in a single transaction.
In this link explain how can be do it.
https://learn.microsoft.com/en-us/powerapps/developer/data-platform/webapi/execute-batch-operations-using-web-api#when-to-use-batch-requests
Please let me know wtih anything
If you want to regularly ingest data (1000 rows) into Dataverse (CDS), then use Dataflows. The following link to MS Docs describes how to set up scheduled bulk data updates. It is therefore a pull rather than push model.
https://learn.microsoft.com/en-us/powerapps/maker/data-platform/create-and-use-dataflows
I have created a logic app with the goal of pulling data from a container within cosmosdb (with a query), looping over the results and then pushing this data into CRM (or Common Data Service). When the data is pushed to CRM, an ID will be generated. I wish to then update cosmosdb with this new ID. Here is what I have so far:
This next step is querying for the data within our cosmosdb database and selecting all IDS with a length that is greater than 15. (This tells us that the ID is not yet within the CRM database)
Then we loop over the results and push this into CRM (Dynamics365 or the Common Data Service)
Dilemma: The first part of this process appears to be correct, however, I want to make sure that I am on the right track with this. Furthermore, once the data is successfully pushed to CRM, CRM automatically generates an ID for each record. How would I then update cosmosDB with the newly generated IDs?
Any suggestion is appreciated
Thanks
I see a red flag in your approach here with this query with length(c.id) > 15. This is not something I would do. I don't know how big your database is going to be but generally not very performant to do high volumes of cross partition queries, especially if the database is going to keep growing.
Cosmos DB already provides an awesome streaming capability so rather than doing this in a batch I would use Change Feed and use that to accomplish whatever your doing here in your Logic App. This will likely give you better control of the process and likely allow you to get the id back out of your CRM app to insert back into Cosmos DB.
Because you will be writing back to Cosmos DB, you will need a flag to ignore the update in Change Feed when the item is updated.
In my Azure CosmosDB, that I use with the Gremlin API there is one database called graphdb with several {DocumentCollections}.
I would like to copy a selected set of Vertices and Edges from one collection (graphdb) to another (Tintin).
I managed to do this by transferring all data via the client, but it would be much easier if data stayed in Azure. Thus I tried some SQL in the Azure portal like:
SELECT *
INTO Tintin
FROM graphdb;
However, this seems unsupported.
Now you cannot join multiple collections and you query violates this rule.
But I think +1 for your idea, you should post it on https://feedback.azure.com/
I've been working on a Xamarin.Forms application in Visual Studio using Azure for the backend for a while now, and I've come across a really strange issue.
Please note, that I am following the methods mentioned in this blog
For some strange reason the PullAsync() method seems to have some bizarre problems. Any data that I create and sync will only be pulled by PullAsync() from that solution. What I mean by that is that if I create another solution that accesses the exact same backend, it can perform it's own create/sync data, but will not bring over the data generated by the other solution, even though they both seem to have the exact same access. This appears to be some kind of a security feature/issue, but I can't quite make sense of it.
Has anyone else encountered this at all? Was there a work-around at all? This could potentially cause problems down the road if I were to ever want to create another solution that accesses the same system/data for whatever reason.
For some strange reason the PullAsync() method seems to have some bizarre problems. Any data that I create and sync will only be pulled by PullAsync() from that solution.
According to your provided tutorial, I found that the related PullAsync is using Incremental Sync.
await coffeeTable.PullAsync("allCoffees", coffeeTable.CreateQuery());
Incremental Sync:
the first parameter to the pull operation is a query name that is used only on the client. If you use a non-null query name, the Azure Mobile SDK performs an incremental sync. Each time a pull operation returns a set of results, the latest updatedAt timestamp from that result set is stored in the SDK local system tables. Subsequent pull operations retrieve only records after that timestamp.
Here is my test, you could refer to it for a better understanding of Incremental Sync:
Client : await todoTable.PullAsync("todoItems-02", todoTable.CreateQuery());
The client SDK would check if there has a record with the id equals deltaToken|{table-name}|{query-id} from the __config table of your SQLite local store.
If there has no record, then the SDK would send a request as following for pulling your records:
https://{your-mobileapp-name}.azurewebsites.net/tables/TodoItem?$filter=(updatedAt%20ge%20datetimeoffset'1970-01-01T00%3A00%3A00.0000000%2B00%3A00')&$orderby=updatedAt&$skip=0&$top=50&__includeDeleted=true
Note: the $filter would be set as (updatedAt ge datetimeoffset'1970-01-01T00:00:00.0000000+00:00')
While there has a record, then the SDK would pick up the value as the latest updatedAt timestamp and send the request as follows:
https://{your-mobileapp-name}.azurewebsites.net/tables/TodoItem?$filter=(updatedAt%20ge%20datetimeoffset'2017-06-26T02%3A44%3A25.3940000%2B00%3A00')&$orderby=updatedAt&$skip=0&$top=50&__includeDeleted=true
Per my understanding, if you handle the same logical query with the same query id (non-null) in different mobile client, you need to make sure the local db is newly created by each client. Also, if you want to opt out of incremental sync, pass null as the query ID. In this case, all records are retrieved on every call to PullAsync, which is potentially inefficient. For more details, you could refer to How offline synchronization works.
Additionally, you could leverage fiddler for capturing the network traces when you invoke the PullAsync, in order to troubleshoot your issue.
We've got an application in Django running against a PGSQL database. One of the functions we've grown to support is real-time messaging to our UI when data is updated in the backend DB.
So... for example we show the contents of a customer table in our UI, as records are added/removed/updated from the backend customer DB table we echo those updates to our UI in real-time via some redis/socket.io/node.js magic.
Currently we've rolled our own solution for this entire thing using overloaded save() methods on the Django table models. That actually works pretty well for our current functions but as tables continue to grow into GB's of data, it is starting to slow down on some larger tables as our engine digs through the current 'subscribed' UI's and messages out appropriately which updates are needed as which clients.
Curious what other options might exist here. I believe MongoDB and other no-sql type engines support some constructs like this out of the box but I'm not finding an exact hit when Googling for better solutions.
Currently we've rolled our own solution for this entire thing using
overloaded save() methods on the Django table models.
Instead of working on the app level you might want to work on the lower, database level.
Add a PostgreSQL trigger after row insertion, and use pg_notify to notify external apps of the change.
Then in NodeJS:
var PGPubsub = require('pg-pubsub');
var pubsubInstance = new PGPubsub('postgres://username#localhost/tablename');
pubsubInstance.addChannel('channelName', function (channelPayload) {
// Handle the notification and its payload
// If the payload was JSON it has already been parsed for you
});
See that and that.
And you will be able to to the same in Python https://pypi.python.org/pypi/pgpubsub/0.0.2.
Finally, you might want to use data-partitioning in PostgreSQL. Long story short, PostgreSQL has already everything you need :)