parmap | Easy to use map and starmap python equivalents | Architecture library
kandi X-RAY | parmap Summary
kandi X-RAY | parmap Summary
Easy to use map and starmap python equivalents
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Top functions reviewed by kandi - BETA
- Apply a function to an iterable .
- Map a function asynchronously .
- Add deprecated keyword arguments to kwargs .
- Wraps an asynchronous map .
- Apply a function to an iterable .
- Progress the progress bar .
- Apply a function to each iterable .
- Map a function over an iterable .
- Create the multiprocessing pool .
- Serialize a function to a list .
parmap Key Features
parmap Examples and Code Snippets
Lines of Code : 52License : Strong Copyleft (CC BY-SA 4.0)
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import numpy as np
import multiprocessing as mp
path = 'C:\\Users\\sys\\PycharmProjects\\MPtest\\*.gwf'
filenames = [os.path.basename(x) for x in glob.glob(path)]
filelist= sorted(filenames, key=lambda x: float(re.findall("(\d+)", x)[0#If you can't use spark2.4 or get stuck, please leave a comment.
from pyspark.sql import functions as F
from pyspark.sql.window import Window
df=spark.createDataFrame(data)
w=Window().partitionBy("id").orderBy((F.col("date")).cast("lcv2.imwrite(r'C:\Users\Desktop\result (' + str(i) + ').png', result) #result is 16bit image
with multiprocessing.Pool(processes=N) as pool:
rets = pool.map(func, args)
jobs = []
for _ in range(num_jobs):
job = multiprocessing.Process(target=func, args=args)
job.start()
jobs.append(job)
# Community Discussions
Trending Discussions on parmap
QUESTION
We are running Spark 3.1.1 on Kubernetes in client mode.
We are a simple scala spark application that loads parquet files from S3 and aggregates them:
...ANSWER
Answered 2021-Aug-08 at 09:30Well, that's was an easy one.
I had to catch all exceptions to ensure that spark context is being closed no matter what:
QUESTION
Suppose I have 3 simple SparkML models that will use the same DataFrame as input, but are completely independent of each other (in both running sequence and columns of data being used).
The first thing that pops to my mind is that just create a Pipeline array with the 3 models in the stages array, and running the overarching fit/transform to get the full prediction and such.
BUT, my understanding is that because we're stacking these models in a single pipeline as a sequence, Spark will not necessarily run these models in parallel, even though they are completely independent of each other.
That being said, Is there a way to fit/transform 3 independent models in parallel? The first thing I thought of was to create a function/object that makes a pipeline, and then running a map or parmap where I will run the 3 models in the map function, but I don't know if that'll take advantage of the parallelism.
These are not really cross validation type models either; the workflow I'd like is:
- Prep my dataframe
- The dataframe will have let's say 10 columns of 0-1s
- I will run a total of 10 models, where each model will take one of the 10 columns, filter the data if that column val == 1, and then fit/transform.
Hence, the independence comes from the fact that these individual models are not chained and can be run as-is.
Thanks!
...ANSWER
Answered 2021-Jan-04 at 10:08The SparkML supports parallel evaluation for the same pipeline https://spark.apache.org/docs/2.3.0/ml-tuning.html. But for different models I haven´t seen any implementation yet. If you use a parallel collection to wrap your pipelines the first model that it´s fitted get the resources of your Spark App. Maybe with the RDD api you could do something, but with Spark ML... training different pipelines in parallel and to spawn different parallel stages each of them with a different pipeline model at the moment it is not possible.
QUESTION
I have the following test data:
...ANSWER
Answered 2020-Apr-02 at 21:02This will work for spark2.4(array_distinct only in 2.4). I used the DataFrame you provided, and spark inferred the column date to be of type TimestampType. For my spark code to work, the column date has to be of type TimestampType. The window function travels back 2 days, based on same id, and collects a list of names. If the number of distinct names are >1, then it inputs 1, otherwise 0.
The code below uses rangeBetween(-(86400*2),Window.currentRow) which basically means that to include currentRow and then go back 2 days, so if current row date is 3, it will include [3,2,1]. if you only want current row date and 1 day before, you could replace 86400*2 with 86400*1
QUESTION
This is a follow up to this question: How to synchronously execute an Lwt thread
I am trying to run the following piece of code:
...ANSWER
Answered 2020-Mar-25 at 09:08The issue is that the calls to server_content2, which start the requests, occur in the parent process. The code then tries to finish them in the child processes spawned by Parmap. Lwt breaks here: it cannot, in general, keep track of I/Os across a fork.
If you store either thunks or arguments in the list yolo, and delay the calls to server_content2 so that they are done in the child processes, the requests should work. To do that, make sure the calls happen in the callback of Parmap.pariter.
QUESTION
Is there any way to concatenate Parmap sequences similar to build-in lists in OCaml ?
Specifically I want to do something that would work like this:
...ANSWER
Answered 2020-Feb-04 at 00:11I assume you're referring to this parmap.
Such an operation, as I understand, would not really profit from parallelization, since you can still only walk through the linked list one element at a time. What about your application prevents you from doing the following?
QUESTION
i = 2 #int
cv2.imwrite([r'C:\Users\Desktop\result (' + str(i) + ').png'], result) #result is 16bit image
ANSWER
Answered 2020-Jan-16 at 06:16cv2.imwrite takes first argument as a string, not a list. You should fix your code as following:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install parmap
You can use parmap like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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