I have a sufficiently large dataset that I would like to bulk index the JSON objects in AWS OpenSearch.
I cannot see how to achieve this using any of: boto3, awswrangler, opensearch-py, elasticsearch, elasticsearch-py.
Is there a way to do this without using a python request (PUT/POST) directly?
Note that this is not for: ElasticSearch, AWS ElasticSearch.
Many thanks!
I finally found a way to do it using opensearch-py, as follows.
First establish the client,
# First fetch credentials from environment defaults
# If you can get this far you probably know how to tailor them
# For your particular situation. Otherwise SO is a safe bet :)
import boto3
credentials = boto3.Session().get_credentials()
region='eu-west-2' # for example
auth = AWSV4SignerAuth(credentials, region)
# Now set up the AWS 'Signer'
from opensearchpy import OpenSearch, RequestsHttpConnection, AWSV4SignerAuth
auth = AWSV4SignerAuth(credentials, region)
# And finally the OpenSearch client
host=f"...{region}.es.amazonaws.com" # fill in your hostname (minus the https://) here
client = OpenSearch(
hosts = [{'host': host, 'port': 443}],
http_auth = auth,
use_ssl = True,
verify_certs = True,
connection_class = RequestsHttpConnection
)
Phew! Let's create the data now:
# Spot the deliberate mistake(s) :D
document1 = {
"title": "Moneyball",
"director": "Bennett Miller",
"year": "2011"
}
document2 = {
"title": "Apollo 13",
"director": "Richie Cunningham",
"year": "1994"
}
data = [document1, document2]
TIP! Create the index if you need to -
my_index = 'my_index'
try:
response = client.indices.create(my_index)
print('\nCreating index:')
print(response)
except Exception as e:
# If, for example, my_index already exists, do not much!
print(e)
This is where things go a bit nutty. I hadn't realised that every single bulk action needs an, er, action
eg "index", "search" etc. - so let's define that now
action={
"index": {
"_index": my_index
}
}
The next quirk is that the OpenSearch bulk API requires Newline Delimited JSON (see https://www.ndjson.org ), which is basically JSON serialized as strings and separated by newlines. Someone wrote on SO that this "bizarre" API looked like one designed by a data scientist - far from taking offence, I think that rocks. (I agree ndjson is weird though.)
Hideously, now let's build up the full JSON string, combining the data and actions. A helper fn is at hand!
def payload_constructor(data,action):
# "All my own work"
action_string = json.dumps(action) + "\n"
payload_string=""
for datum in data:
payload_string += action_string
this_line = json.dumps(datum) + "\n"
payload_string += this_line
return payload_string
OK so now we can finally invoke the bulk API. I suppose you could mix in all sorts of actions (out of scope here) - go for it!
response=client.bulk(body=payload_constructor(data,action),index=my_index)
That's probably the most boring punchline ever but there you have it.
You can also just get (geddit) .bulk()
to just use index=
and set the action to:
action={"index": {}}
Hey presto!
Now, choose your poison - the other solution looks crazily shorter and neater.
conn = wr.opensearch.connect(
host=self.hosts, # URL
port=443,
username=self.username,
password=self.password
)
def insert_index_data(data, index_name='stocks', delete_index_data=False):
""" Bulk Create
args: body [{doc1}{doc2}....]
"""
if delete_index_data:
index_name = 'symbol'
self.delete_es_index(index_name)
resp = wr.opensearch.index_documents(
self.conn,
documents=data,
index=index_name
)
print(resp)
return resp
I have used below code to bulk insert records from postgres into OpenSearch ( ES 7.2 )
import sqlalchemy as sa
from sqlalchemy import text
import pandas as pd
import numpy as np
from opensearchpy import OpenSearch
from opensearchpy.helpers import bulk
import json
engine = sa.create_engine('postgresql+psycopg2://postgres:postgres@127.0.0.1:5432/postgres')
host = 'search-xxxxxxxxxx.us-east-1.es.amazonaws.com'
port = 443
auth = ('username', 'password') # For testing only. Don't store credentials in code.
# Create the client with SSL/TLS enabled, but hostname verification disabled.
client = OpenSearch(
hosts = [{'host': host, 'port': port}],
http_compress = True,
http_auth = auth,
use_ssl = True,
verify_certs = True,
ssl_assert_hostname = False,
ssl_show_warn = False
)
with engine.connect() as connection:
result = connection.execute(text("select * from account_1_study_1.stg_pred where domain='LB'"))
records = []
for row in result:
record = dict(row)
record.update(record['item_dataset'])
del record['item_dataset']
records.append(record)
df = pd.DataFrame(records)
#df['Date'] = df['Date'].astype(str)
df = df.fillna("null")
print(df.keys)
documents = df.to_dict(orient='records')
#bulk(es ,documents, index='search-irl-poc-dump', raise_on_error=True)\
#response=client.bulk(body=documents,index='sample-index')
bulk(client, documents, index='search-irl-poc-dump', raise_on_error=True, refresh=True)
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