Does using external RAM work while running predictive models? - classification

I am trying to run predictive modeling on large volume of data and this requires large amount of RAM (>8gb which i currently have on my laptop).
Just wanted to check if any of you encountered similar problem ? I recently came across external RAM for windows 7 OS - wondering if any of you have tried it ?
Does it help if i get an "readyboost RAM" of say 25gb or higher to solve this problem ?
Please let me know if its worth investing in external readyboost RAMs ? Thanks.

I use a 16Gb Memory stick on a 4Gb laptop - Windows 7 will only use 4Gb.. not sure if physical memory and the amount of Readyboost memory that Windows will use are related. I must say it does make a difference. Worth a look with USB memory sticks being so cheap now.
It certainly seems to speed up program startup and makes the system feel more responsive. A good cheap investment.

Related

manipulation of processor speed without changing the processor

is it possible to replace a ram with higher storage on a machine with a processor of low speed? is speed of processing increased or decreased.
i want to replace the ram drive of my machine with a higher storage ram so that I can try to manipulate the processor speed without changing the processors, will it work?
Yes. You can use faster RAM, currently up to DDR4-4800MHz. Using higher capacity RAM would also be useful if running out of RAM capacity is what’s slowing you down. Using a high-speed solid-state drive (SSD) would also speed up task that require reading or writing from storage, including booting up the computer and running programs that use a lot of assets on the computer. You can also overclock both your CPU and RAM to make them faster, but this may void your warranty.
Additionally, you can use software. For example, you can use CCleaner to remove useless files which clutter your computer. You can also use it to disable unneeded scheduled tasks that your computer runs. If your computer has a spinning-disc hard drive, then you can try defragmenting it by using the built-in Windows defragger, or you can use the Defraggler program from the same people who make CCleaner. Of course, you can also try deleting programs or files you no longer need or use if it’s limited hard drive capacity that’s slowing you down.
If it’s web browsing that’s slow, you may want to consider using a faster browser, like Google Chrome or Firefox. You can also install browser extensions/add-ons like AdBlock and Ghostery to prevent unneeded things from being loaded on pages, making pages load faster.

Oracle-SQL Developer consumes lot of system's memory. Has anyone faced issues like this. If so is there is solution to avoid this

I'm using 19.2 version of SQL Developer and I have switched from TOAD.
Offlate when I lock up my system and open after an hour or two, I see my system boots up very slowly.
Most of the system's memory is consumed by Oracle SQL developer. Please see attached screenshot.
Is there any way to avoid the above issues?

How to get my VM to run faster?

So I am running a VirtualBox VM for a Big Data Programming class I am currently in. I'm not entirely sure what kind of specifications to mention to provide any insight, but I have around 95GB of memory left on my Macbook Pro. I have to code in Eclipse Luna in the VM, but once the VM is up and running, opening up Eclipse takes an obscene amount of time. Is this a memory issue, and would buying an external hard drive be the best course of action? When I brought this issue to my professor that seemed to be his consensus(its a memory issue), but I wanted to get a wider array of opinions/help.
So it sounds like you have a RAM bottleneck. Try increase the amount of RAM allocated to the virtual machine. In VirtualBox:
Power off your virtual machine in Virtual Box
Select the virtual machine you are using
Click on Settings
Click on System
Increase the amount of RAM "Base Memory" dedicated to the virtual machine
Click Ok.
Note: Be sure to not add so much that you make the host go slower. Try testing with different amounts until it is optimal performance.
Here is a possibly related resource to help you resolve your problem:
https://forums.virtualbox.org/viewtopic.php?f=8&t=39368

Hardware requirements for eclipse (indigo) on windows 7 32 bit

How much ram and processing power are required to run eclipse smoothly?
I plan to build plugins by extending EMF, GEF.
If you want to be confortable to build plugins, 2GB of RAM is a minimum since you would need multiple Eclipse instances (at least the instance where you have the code of the plugin and the instance where your plugin is running). For the processor, pretty much anything released in the last 4 years (except low end processor) and you're good.
I had a Core 2 Duo with 2GB of RAM a year ago and while it was a bit slow from time to time, I could do my job with 2/3 Eclipse instances. Now with a Core i7 and 6GB, I run daily with 6+ Eclipse instances without feeling any problem.
Stephane Begaudeau
The minimum requirement (2gb) mentioned for eclipse is meant for capability of using it. More Ram is good but less is punishing.
For Eclipse Plugin development, I suggest 8gb of Ram. The CPU choice depends on budget. I had i5 3rd gen and I'm sure it would handle plugin development easily. I won't suggest anything lower than i5 3rd gen or i3 5th gen or ryzen 3 2nd gen or ryzen 5 1st gen.
With my experience I'm telling. When I open 1 extra eclipse instance, few browsers tabs, few more applications like postman, the ram usage spikes to 90+ despite of having 8gb ram. Also, I've octa core machine and sometimes I'm able to utilise it fully 100%. Hence, more is good, decide according to budget.
You must not cut cost in RAM. 8gb is the sweet spot for your need. 4gb will perform slow for sure unless your usage is very low like using only eclipse.
Eclipse java code responsible for long time operations(index update) is mostly singlethreaded, so it is 2-core(there is no one core proc on the market with normal power), i think i3 and overclocked as high as possible. 4gb of cheap ram is quite enough, you don't need fast ram for that. I've also suggested small size SSD raid for HDD is you have enough money. But actully it is not about hardware. It is about eclipse algorithms, memory management, bugs and usability.

Is running postgresql in memory a good idea?

Recently we are working on migrate our software from general PC server to a kind of embedded system which use Disk on module (DOM) instead of hard disk drive.
My colleague insist that as DOM could only support about 1 million times of write operation, we should running our database entirely in a RAM disk and backup the database to DOM.
There 3 ways to trigger the backup :
User trigger
Every 30 minutes
Every time when there is some add/update/delete operation in database
As we expecte that user will only modify the database when system is installed, I think maybe postgresql would not write that often.
But I don't know much about postgresql, I can not judge if it worth all this trouble and which approach is better.
What do you think about it?
The problem of wearing out SSDs can be alleviated by whatever firmware the SSD has. Sometimes those chipsets don't do it well, or leave the responsibility to someone else. In this case, you can use a filesystem designed to do wear levelling by itself. UBIFS or LogFS are suitable filesystems.
Assuming that the claim about the DOM write cycles is true, which I can't comment on, then this won't work very well. PostgreSQL assumes that it can write whatever it wants whenever it wants (even if no logical updates are happening), and you have no real chance of making it go along with the 3 triggers that you mention.
What you could do is have the entire thing run on a RAM disk and have some operating system process back this up atomically to permanent storage. This needs careful file system and kernel support. This could work if your device is on most of the time, but probably not so well if it's the sort of thing that you switch on and off like a TV, because the recovery times could be annoying.
Alternatives are using either a more embedded-like RDBMS such as SQLite, or using a storage system that can handle PostgreSQL, like the recent solid state drives, although some SSDs have bogus cache settings that might make them unsuitable for PostgreSQL.