tcmalloc | This repository contains the TCMalloc C++ code

I've found a related question where the same author found the solution, please click here to see:

As a side note, if you have the same error, and provided solutions does not work, please, follow the link and try this answer,but paying special attention to remove both lib and log files created by mongodb,

Why the router would require more memory?

If there is any query in the sharded cluster where the system needs to do a scatter gather then merging activity is taken care of by the mongos itself.

For example I am running a query db.collectionanme.find({something : 1})

If this something field here is not the shard key itself then by default it will do a scatter gather, use explainPlan to check the query. It does a scatter gather because mongos interacts with config server and realises that it doesn't have information for this respective field. {This is applicable for a collection which is sharded}

To make things worse, if you have sorting operations where the index cannot be used then even that now has to be done on the mongos itself. Sorting operations have to block the memory segment to get the pages together based on volume of data then sort works, imagine the best possible Big O for a sorting operation here. Till that is done the memory is blocked for that operation.

What you should do?

Based on settings (your slowms setting, default should be 100ms), check the logs, take a look at your slow queries in the system. If you see a lot of SHARD_MERGE & in memory sorts taking place then you have your culprit right there.

And for quick fix increase the Swap memory availability and make sure settings are apt.

All the best.

The s field in each log object is the severity of the message: I = informational, W = warning, E = Error.

If you look for the first error in that log, you will see it is:

In MongoDB, users are stored in databases but a database (or databases) that a user has access to doesn't need to be the same as the database in which that user is stored.

The database in which the user is stored is called the authentication database. This is configured via the authSource URI option and various language-specific driver options, as well as the --authenticationDatabase mongo shell option.

The error message says that you are authenticating against the test database. Your earlier shell command shows an attempt to authenticate against the admin database.

Review which database the user was created in and ensure that you use the same database during authentication.

Your session ran out of all available RAM. You can purchase Colab Pro to get extra RAM or you can use a Higher RAM machine and use the Neural Network there

Probably the problem is a bug in DataGrip or its driver.

SOLUTION: Using Compass or MongoDB Shell it works

Alpine uses musl for its C library. You can either use a different non-alpine based image such as node:12-buster-slim or any of the other non-Alpine tags here, or try to get it to work by setting up glibc with the instructions here. Using a Debian or Ubuntu based image would be the easiest way forward.

This log output is called "structured log output" and is the only log format of MongoDB as of 4.4. Previous versions used the human-readable log format.

There are tools under development to make this log output human-readable:

• https://github.com/markbenvenuto/mrlog
• Another one that I can't recall at the moment

Seems to me that you performed unclean shutdown of mongod, possibly after it was already running as a RS node, and you got a rollback. At this point the database refuses to start as an RS node since any data rolled back will be lost.

Since you don't have any nodes to resync from, I suggest restoring the standalone data directory that you started with out of a backup (you've taken one, right?) and proceeding with the conversion once again, this time taking care to gracefully shut down mongod until you have an operational replica set with multiple nodes.

Alternatively you can try launching a standalone mongod from this data directory, using mongodump to get a complete data dump, create a new standalone deployment, mongorestore the data into it, then repeat the conversion process to RS node.