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{
    "RECH0": {
        "HHID": "Case identification uniquely identifies each household. In most surveys, this is constructed by concatenating the cluster or sample point number and the household number, but in some surveys this may be the questionnaire number taken from the front page of the questionnaire.",
        "HV000": "Alphabetic country code to identify the survey from which the data were collected. The code is based on an international standard code. This variable is 3 characters in length, with the third character indicating the format of the recode file used for this survey. For all surveys in DHS VII following this standard, this code will be 7. For example: DR7 is the Dominican Republic, HT7 is Haiti and KH7 is Cambodia.",
        "HV001": "Cluster number is the number identifying the sample point as used during the fieldwork. This variable may be a composite of several variables in the questionnaire. If so, the non- standard variables are included in RECH3 as country-specific variables.",
    

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{
    "RECH0": {
        "HHID": "Case identification uniquely identifies each household. In most surveys this is constructed by concatenating the cluster or sample point number and the household number, but in some surveys this may be the questionnaire number taken from the front page of the questionnaire.",
        "HV000": "Alphabetic country code to identify the survey from which the data were collected. The code is based on an international standard code. This variable is 3 characters in length, with the third character indicating the format of the recode file used for this survey. For all surveys in DHS VI following this standard, this code will be 6. For example: DR6 is the Dominican Republic, HT6 is Haiti and KH6 is Cambodia.",
        "HV001": "Cluster number is the number identifying the sample point as used during the fieldwork. This variable may be a composite of several variables in the questionnaire. If so, the non- standard variables are included in RECH3 as country-specific variables.",
      

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# Convert xml to json/parquet and stores them in TEMP_DIR
# Column names are modified to remove "@"" at the beginning for convenience
# Transforms tags column of posts into a list
# Uses pandas joins and groupby features do one-one and one-many joins


import xmltodict
import json
import simplejson
import os

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{
    "Id": 1,
    "PostTypeId": 1,
    "AcceptedAnswerId": 52,
    "CreationDate": "2017-02-28T16:47:57.887",
    "Score": 19,
    "ViewCount": 407,
    "Body": "<p><a href=\"https://jenkins.io/\" rel=\"nofollow noreferrer\">Jenkins</a> is a fork of <a href=\"http://hudson-ci.org/\" rel=\"nofollow noreferrer\">Hudson</a>.</p>\n\n<p>What are the benefits/advantages of using Jenkins over Hudson for a small private business?</p>\n",
    "OwnerUserId": 3,
    "LastEditorUserId": 210,

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from flask import Flask
from elasticapm.contrib.flask import ElasticAPM

from flask import request
app = Flask(__name__)
app.config['ELASTIC_APM'] = {
    'SERVICE_NAME': 'flask',
    'SERVER_URL': 'https://<apm-server-ip/dns>.com:8200',
    'SERVER_CERT': 'path to elk.example.com/elk.example.com.crt',
    'SERVER_TIMEOUT': '5s',

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apm-server:
  host: "0.0.0.0:8200"
  auth:
    secret_token: 'secret token generated using openssl or any other string'
  ssl:
    enabled: true
    certificate: '/usr/share/apm-server/certs/elk.example.com/elk.example.com.crt'
    key: '/usr/share/apm-server/certs/elk.example.com/elk.example.com.key'

output.elasticsearch:

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server.ssl.enabled: true
server.ssl.certificate: '/home/ubuntu/certs/elk.example.com/elk.example.com.crt'
server.ssl.key: '/home/ubuntu/certs/elk.example.com/elk.example.com.key'

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wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-8.4.1-linux-x86_64.tar.gz
tar -zxf elasticsearch-8.4.1-linux-x86_64.tar.gz
cd elasticsearch-8.4.1/
./bin/elasticsearch-certutil ca --pem
unzip elastic-stack-ca.zip
./bin/elasticsearch-certutil cert --ca-cert ca/ca.crt --ca-key ca/ca.key --pem --name elk.example.com
unzip certificate-bundle.zip
cd ../