partition | A fast and flexible framework for data reduction in R | Machine Learning library

Pythons multiprocessing package is limited to shared memory parallelization. It spawns new processes that all have access to the main memory of a single machine.

You cannot simply scale out such a software onto multiple nodes. As the different machines do not have a shared memory that they can access.

To run your program on multiple nodes at once, you should have a look into MPI (Message Passing Interface). There is also a python package for that.

Depending on your task, it may also be suitable to run the program 4 times (so one job per node) and have it work on a subset of the data. It is often the simpler approach, but not always possible.

cleaner-offset-checkpoint is in kafka logs directory. This file keeps the last cleaned offset of the topic partitions in the broker like below.

You can form a partition key by concatenating multiple property values into a single artificial partitionKey property.

Please follow the steps given in below page: https://www.c-sharpcorner.com/article/understanding-partitioning-and-partition-key-in-azure-cosmos-db/

Let me know if it helps.

All the best!

There is no endpoint that just lists partitioned state for all db's, however the /_dbs_info endpoint is close enough with a little processing.

Here is a naïve script I spun up using nano and nodejs 10. The script displays database names, prefixed with an asterisk (*) if the database is partitioned.

Azure Cosmos db is only supporting Unicode or ASCII in x-ms-documentdb-partitionkey while github.com/vippsas/go-cosmosdb package is using json.Marshal which internally transforms Unicode to Chinese characters automatically.

The only way to solve it is using English as partition key when creating documents.

Looks the question was solved by @Larnu's comment, just add it as an answer to close the question.

If you are using Azure SQL Database, then what the error is telling you is true. Azure SQL Databases are what are known as Partially Contained databases; things like their USER objects have their own Password and the LOGIN objects on the server aren't used for connections. The CONNECTION permission is a server level permission, and thus not supported in Azure SQL Databases.

Create a CTE that returns for each Block_id the step of the first John.
Then join the table to the CTE:

You need to pair down the customers first so there is only one record per customer:

If I understand correctly, you want a cumulative count(distinct) as a window function. Snowflake does not support that directly, but you can easily calculate it using row_number() and a cumulative sum: