I'm moving data from blob storage to cosmos DB using data factory
I have a container with a few thousand rows of data, I would like to load more data to this container but do not want to duplicate any rows. How can I check if that data is already in the container and if so skip that specific data and continue loading?
I'm thinking something along the line of a stored procedure but I'm unsure.
You can achieve this by Data Flow in Azure Data Factory.
Add two source, one is your Blob Storage container, another one is your destination container in Cosmos DB. Then use Exists transformation. Finally sink to your Cosmos DB container.
Screenshot of Data Flow:
Related
I don't know why but I can not see the stored procedures appear when I connect the database to Tableau (I use MariaDB). I can only see the data tables.
Anyone has the same problems with me? I am a newbie so I am not sure if my description is clear or not.
Use the stored procedures.
I found that Tableau does not connect to stored processes and that one way around this is that when you connect to your server, you should use the initial query function. Once you log in, grab Custom SQL and for that script simply use
select * from #nameoftemptable
and Execute.
I'm working on fluentd setup in kubernetes. In kubernetes I have a number of applications which are writing some logs into stdout. I can filter, parse, and send logs to azure blob storage. But I want the logs from blob storage to be ingested into azure data explorer cluster. In data explorer cluster I have a database and table which has some schema defined, already. The question is how do I modify event from fluentd in such a way that it's going to meet the table schema? Is it possible at all? Maybe there are some alternative ways of creating such setup?
Take a look at ingestion mappings, you can pick the properties that you care about and route them to the applicable columns and when a new property arrives you can change the mapping and the table schema will automatically be updated.
Yes it is possible to do this. You can ingest data stored in your blob to a custom table on azure data explorer. Refer this link
https://learn.microsoft.com/en-us/azure/data-explorer/ingest-json-formats?tabs=kusto-query-language#ingest-mapped-json-records
The below is an example where i ingest a JSON document stored in blob to a table in ADX
.ingest into table Events ('https://kustosamplefiles.blob.core.windows.net/jsonsamplefiles/simple.json') with '{"format":"json", "ingestionMappingReference":"FlatEventMapping"}'
If the schema is difficult to parse, i would recomment to ingest first to a raw table(Source Table). Then you can have a update policy to move this data into different tables after parsing. You can check this link to understand about Update policy
Consider using the ability to listen on blobs landing in storage using the event grid mechanism. Check out https://learn.microsoft.com/en-us/azure/data-explorer/ingest-data-event-grid-overview
I need to send data from snowflake to neo4j whenever newly transformed data is available in a snowflake table. What is the best way to do this?
I am thinking of using snowalert to notify an updater service which will then pull new data from the snowflake table and push it to neo4j. Is there a better solution to this problem?
You can use a combination of methods from APOC library to load data from Snowflake to neo4j directly.
https://neo4j.com/labs/apoc/4.3/overview/apoc.periodic/apoc.periodic.repeat/
https://neo4j.com/labs/apoc/4.3/overview/apoc.periodic/apoc.periodic.iterate/
https://neo4j.com/labs/apoc/4.3/overview/apoc.load/apoc.load.jdbc/
As part of one of the requirements in our project we need to connect to a DB based on input in the UI and then fetch the result accordingly. Now this db can be on different db server or in the same db server it can be a different schema.
We are looking to do it in the most efficient way.
One of the ways we have figured out is having the db connection information (like db server, schema etc) in separate properties files. Based on the input from the UI, we pass the input to a db factory that will read the corresponding properties file and will return the corresponding db connection if it already exists, if it doesn't then it will create a new connection and will return it.
We are using spring; we use weblogic for application deployment.
The most efficient way would be to let the respective functions "know" where to look for the requested data. But that's a lot of work in advance.
If the schemes describe similar data (e.g. address data), think about merging the data or the implementation of an frontend/proxy. Both ways would delegate the "looking for data" to the DB-Server(s) which should be able to handle each request way faster and more efficient than any program-logic.
I am developing a sample application with core data with a entity which has two attribute-ID and name.For ID I have set the data type as transformable .After a value for ID is stored in database,Can I pull the transformed ID from the DB and get back the ID?(Not Through the code, by opening the DB in SQLite manager and pulling out from the ID column).Is there a way to check what is stored in DB manually without executing code?
Thanks in advance
You can copy the DB from the device to your machine. I use iExplorer to do this. The best way to view/edit the DB from there is Base, but Firefox has a FREE plugin called SQLite Manager.