Source code for nordlys.core.retrieval.indexer_mongo

Mongo Indexer

This class is a tool for creating an index from a Mongo collection.

To use this class, you need to implement :func:`callback_get_doc_content` function.
See :mod:`` for an example usage of this class.

:Author: Faegheh Hasibi
from nordlys.core.retrieval.elastic import Elastic
from import Mongo
# from nordlys.core.utils.logging_utils import PLOGGER

[docs]class IndexerMongo(object): def __init__(self, index_name, mappings, collection, model=Elastic.BM25): self.__index_name = index_name self.__mappings = mappings self.__mongo = Mongo(MONGO_HOST, MONGO_DB, collection) self.__model = model
[docs] def build(self, callback_get_doc_content, bulk_size=1000): """Builds the DBpedia index from the mongo collection. To speedup indexing, we index documents as a bulk. There is an optimum value for the bulk size; try to figure it out. :param callback_get_doc_content: a function that get a documet from mongo and return the content for indexing :param bulk_size: Number of documents to be added to the index as a bulk """"Building " + self.__index_name + " ...") elastic = Elastic(self.__index_name) elastic.create_index(self.__mappings, model=self.__model, force=True) i = 0 docs = dict() for mdoc in self.__mongo.find_all(no_timeout=True): docid = Mongo.unescape(mdoc[Mongo.ID_FIELD]) # get back document from mongo with keys and _id field unescaped doc = callback_get_doc_content(Mongo.unescape_doc(mdoc)) if doc is None: continue docs[docid] = doc i += 1 if i % bulk_size == 0: elastic.add_docs_bulk(docs) docs = dict() / 1000) + "K documents indexed") # indexing the last bulk of documents elastic.add_docs_bulk(docs)"Finished indexing (" + str(i) + " documents in total)")