title: improve python elasticsearch performance
body: <p>i am new in python and Elasticsearch
  i write a python code that read data from very large json file and index some attributes in Elasricsearch. </p>
  
  <pre><code>import elasticsearch
  import json
  es = elasticsearch.Elasticsearch()  # use default of localhost, port 9200
  with open('j.json') as f:
      n=0
      for line in f:
          try:
              j_content = json.loads(line)
              event_type = j_content['6000000']
              device_id = j_content['6500048']
              raw_event_msg= j_content['6000012']
              event_id = j_content["0"]
              body = {
                  '6000000': str(event_type),
                  '6500048': str(device_id),
                  '6000012': str(raw_event_msg),
                  '6000014': str(event_id),
              }
              n=n+1
              es.index(index='coredb', doc_type='json_data', body=body)
          except:
              pass
  </code></pre>
  
  <p>but it's too slow and i have many free hardware resources. how can i improve performance of code with multi thread or bulk ?</p>