Hello,
I'm encountering a persistent issue with memory RAM exhaustion while running Bitcoin Core on my system.
Here's a brief overview of the problem:
Problem Description:
I have a Bitcoin Core node set up on my system, and I query it every minute using an python script consulting for new blocks.
Using the API /rest/block/<BLOCK-HASH>.json the response is almost immediate but the memory of the daemon process for each block query increases a lot! and there is no release of this memory afterwards.
To solve this problem I must close bitcoin core and reopen it from time to time
But if I use the API /rest/block/notxdetails/<BLOCK-HASH>.json and process the json response and query each tx my memory remains always the same but is very slow.
Is there any solution to this problem?
Thanks!
I'm encountering a persistent issue with memory RAM exhaustion while running Bitcoin Core on my system.
Here's a brief overview of the problem:
Problem Description:
I have a Bitcoin Core node set up on my system, and I query it every minute using an python script consulting for new blocks.
Using the API /rest/block/<BLOCK-HASH>.json the response is almost immediate but the memory of the daemon process for each block query increases a lot! and there is no release of this memory afterwards.
To solve this problem I must close bitcoin core and reopen it from time to time
But if I use the API /rest/block/notxdetails/<BLOCK-HASH>.json and process the json response and query each tx my memory remains always the same but is very slow.
Is there any solution to this problem?
Thanks!
MEDIUM SOLUTION:
It turns out that I downloaded bitcoind and installed it, created symbolic links to my folders where my blocks are located, ran bitcoind -daemon and ran my scripts, the surprise I had was that my memory barely changed, I consulted more than a thousand blocks and my Memory barely increased 150MB, something quite insignificant considering the last 1000 blocks.
With Bitcoin Core Desktop version (Flathub) querying only one block and full verbosity increased my memory by approximately 100 MB.