Comments (4)
Great question man, also I want to know this questions answers, I think first and last question is most important.
from leveldown.
if Lots of User call ""iteratorStream(db.iterator())"" same time will it able to Provide data?
Yes, up to a point where you have too many active iterators, then you may see that performance goes down. It's best to benchmark it yourself, in the context of your application.
will maxOpenFiles parameter help to solve this?
This will help with large data sets, rather than many readers.
will cacheSize parameter help to solve this?
Possibly.
Will ""iteratorStream(db.iterator())"" use lots of cpu/ram or it will use minimal cpu/ram?
It's a streaming interface, and in the case of leveldown
it reads ahead by only 16 kb at a time, so memory usage will be low unless your individual keys or values are large. CPU usage should be minimal as well.
from leveldown.
is it possible to increase 16 KB to 100kb or more at a time?
from leveldown.
Yes, through the undocumented highWaterMark
option: db.open({ highWaterMark: 100 * 1024 }, ...)
(#468).
from leveldown.
Related Issues (20)
- Leveldown Stream HOT 7
- db.iterator() gt & lt HOT 2
- Inbuilt Encryption HOT 1
- Currency and Parallelism HOT 3
- Snappy compression HOT 4
- Support more than 32bit ApproximateSize bindings HOT 4
- Find key createReadStream HOT 4
- support custom comparison function HOT 1
- Explanation of name in README? eg why is this called "leveldown" HOT 1
- Two Oparation HOT 3
- Possible memory leak in getMany? HOT 6
- Compiling legacy on arm HOT 1
- Question: iterate old entries? HOT 3
- `db.get()` doesn't read from a snapshot HOT 1
- Question: db.put() callback order HOT 2
- Operation ordering guarantee HOT 2
- macOS Catalina build errors HOT 1
- Raspbian Bullseye 64 Bit install error HOT 9
- Android cross-compilation errors HOT 1
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from leveldown.