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############################################################################
# This code shows how to split large text documents along sentence 
# boundaries using NLTK and process each chunk with AWS Translate.
############################################################################
# Be sure to first install nltk and boto3
import nltk.data
import boto3
# Define the source document that needs to be translated
source_document = "My little pony heart is yours..."
# Tell the NLTK data loader to look for resource files in /tmp/

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{
  "tracks": [
    {
      "track_type": "General",
      "count": "331",
      "count_of_stream_of_this_kind": "1",
      "kind_of_stream": "General",
      "other_kind_of_stream": [
        "General"
      ],

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# Tell the NLTK data loader to look for resource files in /tmp/
nltk.data.path.append("/tmp/")
# Download NLTK tokenizers to /tmp/
# We use /tmp because that's where AWS Lambda provides write access to the local file system.
nltk.download('punkt', download_dir='/tmp/')
# Load the English language tokenizer
tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
# Split input text into a list of sentences
sentences = tokenizer.tokenize(transcript)
print("Input text length: " + str(len(transcript)))

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$ aws cloudformation describe-stack-events --stack-name mas1
{
    "StackEvents": [
        {
            "StackId": "arn:aws:cloudformation:us-west-2:773074507832:stack/mas1/e0df81c0-54c7-11e9-9a27-0ae01deb57d8",
            "EventId": "49ea43c0-54c9-11e9-bfc1-064b816f3a4a",
            "StackName": "mas1",
            "LogicalResourceId": "mas1",
            "PhysicalResourceId": "arn:aws:cloudformation:us-west-2:773074507832:stack/mas1/e0df81c0-54c7-11e9-9a27-0ae01deb57d8",
            "ResourceType": "AWS::CloudFormation::Stack",

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[Feb 22, 2019 1:49:45 PM]: Integration test for 'Connection' started.
[Feb 22, 2019 1:49:45 PM]: Using Radoop version 9.1.0.
[Feb 22, 2019 1:49:45 PM]: Running 8 tests: [Fetch dynamic settings, NameNode networking, DataNode networking, YARN services networking, MapReduce, HDFS upload, Radoop jar upload, Import job]
[Feb 22, 2019 1:49:45 PM]: Running test 1/8: Fetch dynamic settings
[Feb 22, 2019 1:49:45 PM]: Retrieving required configuration properties...
[Feb 22, 2019 1:49:45 PM]: Successfully fetched property: hive.execution.engine
[Feb 22, 2019 1:49:45 PM]: Successfully fetched property: yarn.resourcemanager.scheduler.address
[Feb 22, 2019 1:49:45 PM]: Successfully fetched property: yarn.resourcemanager.resource-tracker.address
[Feb 22, 2019 1:49:45 PM]: Successfully fetched property: yarn.resourcemanager.admin.address
[Feb 22, 2019 1:49:45 PM]: Successfully fetched property: yarn.app.mapreduce.am.staging-dir

iandow

-----BEGIN SIGNED MESSAGE-----
clusterid: "5427061983691452296"
version: "4.0"
customerid: "ignore"
issuer: "MapR Technologies"
licType: Demo
description: "MapR Enterprise Trial Edition"
enforcement: HARD
gracePeriod: 0
issuedate: 1550010076

iandow

# Copyright (c) 2009 & onwards. MapR Tech, Inc., All rights reserved
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: test-static-pvc
  namespace: test-csi
spec:
  accessModes:
    - ReadWriteOnce
  resources:

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# Copyright (c) 2009 & onwards. MapR Tech, Inc., All rights reserved
apiVersion: v1
kind: PersistentVolume
metadata:
  name: test-static-pv
  namespace: test-csi
spec:
  accessModes:
  - ReadWriteOnce
  persistentVolumeReclaimPolicy: Delete

iandow

<configuration>
  <property>
    <name>mapreduce.jobhistory.address</name>
    <value>nodec:10020</value>
  </property>
  <property>
    <name>mapreduce.jobhistory.webapp.address</name>
    <value>nodec:19888</value>
  </property>
  <property>

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<configuration>
  <!-- Site specific YARN configuration properties -->
  <property>
    <name>yarn.resourcemanager.hostname</name>
    <value>nodeb</value>
    <description>host is the hostname of the resourcemanager</description>
  </property>
  <property>
    <name>yarn.resourcemanager.recovery.enabled</name>
    <value>true</value>