Elasticsearch ignores mapping when using bulk in Python DSL

Question

I'm trying to upload a CSV file to an elasticsearch index. Let's say the file is something like this (no headers, just data):

bird,10,dog
cat,20,giraffe

This is the code I have:

from elasticsearch_dsl import DocType, Integer, Keyword
from elasticsearch_dsl.connections import connections
from elasticsearch.helpers import bulk
import csv

connections.create_connection(hosts=["localhost"])

class Mapping(DocType):    
    animal1 = Keyword()
    number = Integer()
    animal2 = Keyword()

    class Meta:
        index = "index-name"
        doc_type = "doc-type" 

Mapping.init()
with open("/path/to/file", "r", encoding="latin-1") as f:
    reader = csv.DictReader(f)
    bulk(
        connections.get_connection(),
        (Mapping(**row).to_dict(True) for row in reader)
    )

The problem is that elasticsearch seems to be ignoring the mapping and using the first line of the file as headers (and creating a mapping based on that).

Edit: it really uses my mapping and the first line of the file. The mapping it generates is:

{
  "index-name": {
    "mappings": {
      "doc-type": {
        "properties": {
          "10": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "dog": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "animal1": {
            "type": "keyword"
          },
          "animal2": {
            "type": "keyword"
          },
          "bird": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "number": {
            "type": "integer"
          }
        }
      }
    }
  }
}

If I only create the index without uploading data, the mapping seems fine:

{
  "index-name": {
    "mappings": {
      "doc-type": {
        "properties": {
          "animal1": {
            "type": "keyword"
          },
          "animal2": {
            "type": "keyword"
          },
          "number": {
            "type": "integer"
          }
        }
      }
    }
  }
}

How can I make ES use the given mapping and just that?

`bird 10 dog` looks remarkably off... – Jon Clements Feb 15 '18 at 18:33 — Jon Clements, Feb 15 '18 at 18:33

Lupanoide · Accepted Answer · 2018-02-16T14:43:29.443

Elasticsearch creates a new field with the first element of each row, because you haven't specified a field for the csv data with headers, you haven't specified that 1 element of the tuple is animal1, and the second is animal2 and so on..Try this:

from elasticsearch import Elasticsearch
from elasticsearch import helpers


index_name = "your_index_name"
doc_type = "your_doc_type"
esConnector = Elasticsearch(["http://192.168.1.1:9200/"])
# change your ip here
paramL = []
contatore = 1


with open(args.file, "r", encoding="latin-1") as f:
    for line in f:
       line = line.split(",")
       tripla = {"animal1": line[0], "number": line[1], "animal2": line[2]} 
       ogg={
        '_op_type': 'index',
        '_index': index_name,
        '_type': doc_type,
        '_id': contatore,
        '_source': tripla
            }
        contatore +=1
        paramL.append(ogg)


for success, info in helpers.parallel_bulk(client=esConnector, actions=paramL, thread_count=4):
    if not success: 
        print 'Doc failed', info

How can I do the same but when instead of a .csv I have a list? ```https://stackoverflow.com/questions/62778983/compressor-detection-can-only-be-called-on-some-xcontent-bytes-or-compressed-xc/62779491?noredirect=1#comment111091182_62779491``` — Aizzaac, Jul 10 '20 at 15:32

Elasticsearch ignores mapping when using bulk in Python DSL

1 Answers1