Codigo para demostrar distribuciones de latencia en un servicio de software con distintos algoritmos.
Para instalar el entorno en Linux/Unix:
virtualenv venv
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| apache-beam[aws,gcp,test] | |
| ipython |
This is a set of two sample Beam Pipelines that we use to calculate Pi with a monte carlo algorithm that relies on generating random points in an n-dimentional cube, and validating whether they are located within a circle in that space.
These examples are meant to showcase the use of Beam's Batched DoFns developed by @TheNeuralBit.
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/ expected_outcome_script.txt
Created
November 8, 2022 21:22
expected outcome from first run of image
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| prebuilt_beam_sdk/beam_python_prebuilt_sdk | |
| IMAGES FOR REPO prebuilt_beam_sdk/beam_python_prebuilt_sdk | |
| IMAGES FOR REPO beam-sdk | |
| IMAGES FOR REPO beam_portability | |
| gcr.io/apache-beam-testing/prebuilt_beam_sdk/beam_python_prebuilt_sdk/cachegcr.io/apache-beam-testing/beam-sdk/beam_go_sdk gcr.io/apache-beam-testing/beam-sdk/beam_java11_sdk gcr.io/apache-beam-testing/beam-sdk/beam_java17_sdk gcr.io/apache-beam-testing/beam-sdk/beam_java8_sdk gcr.io/apache-beam-testing/beam-sdk/beam_python3.10_sdk gcr.io/apache-beam-testing/beam-sdk/beam_python3.6_sdk gcr.io/apache-beam-testing/beam-sdk/beam_python3.7_sdk gcr.io/apache-beam-testing/beam-sdk/beam_python3.8_sdk gcr.io/apache-beam-testing/beam-sdk/beam_python3.9_sdkgcr.io/apache-beam-testing/beam_portability/beam_flink1.10_job_server gcr.io/apache-beam-testing/beam_portability/beam_flink1.12_job_server gcr.io/apache-beam-testing/beam_portability/beam_flink1.13_job_server gcr.io/apache-beam-testing/beam_portability/beam_go_sdk gcr.io/apache-beam-testing/beam_portability/b |
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| #include <pthread.h> | |
| #include <stdio.h> | |
| #include <stdlib.h> | |
| #include <unistd.h> | |
| #define MAX_QUEUE_SIZE 10 | |
| typedef struct { | |
| int tag; | |
| char *message; |
This project demonstrates how to put together a list of words for Apache Beam. This list of words is meant to be used to launch a Beam wordle game. The project has the following pieces:
- A Beam Pipeline that scrapes the Beam website in
scrape-beam-words.py. The outputs of this pipeline are:beam_wordle_words.txt*: A long list of words, separated by newline.
beam_wordle_histogram.txt*: A file detailing the frequency in word
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