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#!/bin/bash

repositories=$(aws ecr describe-repositories | jq -r '.repositories[].repositoryName')

for repo in $repositories
do
    # latest image, having a version tag
    latest_image=$(aws ecr describe-images --repository-name $repo --query 'sort_by(imageDetails,& imagePushedAt)[*]' |  jq -r '.[] | select(.imageTags[] | startswith("v")) | "imageDigest=\(.imageDigest),imageTag=\(.imageTags[0])"' 2>/dev/null | tail -n 1 )

    if [ -z "$latest_image" ]; then

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def async_cache(func):
    """
    decorator meant to build singletons, and designed for async coroutines
    :param func:
    :return:
    """
    instances = {}

    @functools.wraps(func)
    async def wrapper(*args, **kwargs):

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Array.from(document.querySelectorAll("[aria-labelledby=detail-header] label").values()).filter(i => i.control.checked ).forEach(i => {i.click()})

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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements.  See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License.  You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*

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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements.  See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License.  You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*

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package ssp

import java.nio.charset.Charset
import java.nio.file.{Files, Paths}

import org.apache.spark.sql.functions.broadcast
import org.apache.spark.sql.streaming.{OutputMode, Trigger}
import org.apache.spark.sql.types.{StringType, StructField, StructType}
import org.apache.spark.sql.{Dataset, SparkSession}
import org.apache.spark.storage.StorageLevel

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Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

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// This code is related to PR https://github.com/apache/spark/pull/17461
// I show how to use the setInitialModel() param of LDA to build a model incrementally, 
// and I compare the performance (perplexity) with a model built in one-shot


import scala.collection.mutable

import org.apache.spark.ml.{Pipeline, PipelineModel}
import org.apache.spark.ml.clustering.{LDA, LDAModel}

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ssh edge_node "hdfs dfs -cat /some/path/part-*" | cat > file

cat file | ssh edge_node "hdfs dfs -put - /target/path"


# think of using a named pipe (mkfifo) to sream directly for application output 
rm -f stream
mkfifo stream

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# grab the kernel module name
lshw -C network 2>&1 | grep wireless | grep driver

sudo modprobe -r ath9k && sudo modprobe ath9k