More error information is needed when using pandas_to_eland()

[walkingmug]

Description:
When uploading a pandas.DataFrame() that contains values of different types to elastic with eland.pandas_to_eland(), it returns a BulkIndexError without specifying why and where.

Reproduction:

1. Install requirements:
   pip install elasticsearch eland pandas
2. Imports:

from elasticsearch import Elasticsearch
import eland as ed
import pandas as pd

3. Connect to Elasticsearch:

client = Elasticsearch(HOST, timeout=120)

4. Create vector dataframes:

pd_df = pd.DataFrame([[True, 'foo'], ['bar', 'baz']], columns=['A', 'B'])

• Note that column A will contain two different types: a boolean True and a text bar.

5. Upload dataframe:

ed.pandas_to_eland(
  pd_df=pd_df,
  es_client=client,
  es_dest_index='test',
  es_if_exists="replace",
  es_refresh=True,
  es_type_overrides={
      "A": {
        "type": "boolean"
      },
      "B": {
        "type": "text"
      }
  },
)

6. Error:

---------------------------------------------------------------------------
BulkIndexError                            Traceback (most recent call last)
[<ipython-input-29-49062063ee82>](https://localhost:8080/#) in <cell line: 2>()
      1 # upload to elasticsearch
----> 2 statista_updated = ed.pandas_to_eland(
      3   pd_df=to_upload,
      4   es_client=client,
      5   es_dest_index='test-statistics',

6 frames
[/usr/local/lib/python3.10/dist-packages/elasticsearch/helpers/actions.py](https://localhost:8080/#) in _process_bulk_chunk_success(resp, bulk_data, ignore_status, raise_on_error)
    272 
    273     if errors:
--> 274         raise BulkIndexError(f"{len(errors)} document(s) failed to index.", errors)
    275 
    276 

BulkIndexError: 1 document(s) failed to index.

• The error BulkIndexError: 1 document(s) failed to index. lacks description of which documents failed to index and why. In datasets with many rows and columns (100k+), it is difficult to pinpoint the issue in order to fix it.

Possible Cause:
Dequeue is currently used to perform bulk upload, which is preventing it from collecting error information on fails. To retrieve error information, for success, info in parallel_bulk(...): is beneficial.

Further Benefits:
By enabling description on errors, all other errors that are not type mismatches will be displayed too. This will help users understand what the problem is and where it is coming from.