Csv parse taking too long using python API

[henriqueluz (Henrique)]

Hello! That's my first post here in elastic discussion area, sorry if any mistake were made.

I'm kinda new using ELK Stack, I'm trying to parse a .CSV file to ElasticSearch using the Python API. The thing is, it's taking way too long to parse just a few logs (312seconds to parse 30000 logs). I'm using ElasticSearch 5-6-3 running on Ubuntu 16.04, 6GB RAM
The main idea is to convert each row into a json and then parse it to Elastic, the code:

import time
import json
import pandas as pd
from elasticsearch import Elasticsearch

class Storage(object):
    
    def __init__(self,user,password):
        
        self.user = user
        self.password = password
        self.es = Elasticsearch(http_auth=(user, password))
        
    def get_info(self, log=False):
        
        info = self.es.info()
        if info:
            print(json.dumps(info, indent=3))
            return info
    
    def index(self, index, doc_type, _id, json):
    
        status = self.es.index(index=index, doc_type=doc_type, id = _id, body=json)
        return status

        
if __name__ == '__main__':
    
    st = Storage('elastic','changeme')
    print(st.get_info())
    df  = pd.read_csv(file_to_parse, low_memory=False)
    aux = df.to_dict('records')
    
    index = 1
    begin = time.time()
    for register in aux:
        
        reg = json.dumps(register)
        res = st.index('someindex','log',index,reg)
        index += 1
        
    print("Finished", time.time() - begin)

What could possibly be improved here?

[Christian_Dahlqvist]

Use the bulk API to send multiple documents per indexing request (docs). This is much more efficient than indexing each document individually.