Python helpers.scan方法代碼示例

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def get(self, spec, fields=None, **kargs):
        """Queries the active index."""
        query = {"query": spec.to_dict()}
        if fields is not None:
            query['_source'] = fields
        for rec in helpers.scan(self.db_client,
                                query=query,
                                index=self.indexes[0],
                                ignore_unavailable=True):
            host = dict(rec['_source'], _id=rec['_id'])
            if 'coordinates' in host.get('infos', {}):
                host['infos']['coordinates'] = host['infos'][
                    'coordinates'
                ][::-1]
            for field in self.datetime_fields:
                if field in host:
                    host[field] = utils.all2datetime(host[field])
            yield host 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def scan(self):
        """
        Turn the search into a scan search and return a generator that will
        iterate over all the documents matching the query.

        Use ``params`` method to specify any additional arguments you with to
        pass to the underlying ``scan`` helper from ``elasticsearch-py`` -
        http://elasticsearch-py.readthedocs.org/en/master/helpers.html#elasticsearch.helpers.scan

        """
        es = connections.get_connection(self._using)

        for hit in scan(
                es,
                query=self.to_dict(),
                index=self._index,
                doc_type=self._doc_type,
                **self._params
            ):
            yield self._doc_type_map.get(hit['_type'], Result)(hit) 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def scan(self):
        """
        Turn the search into a scan search and return a generator that will
        iterate over all the documents matching the query.

        Use ``params`` method to specify any additional arguments you with to
        pass to the underlying ``scan`` helper from ``elasticsearch-py`` -
        https://elasticsearch-py.readthedocs.io/en/master/helpers.html#elasticsearch.helpers.scan

        """
        es = connections.get_connection(self._using)

        for hit in scan(
                es,
                query=self.to_dict(),
                index=self._index,
                **self._params
        ):
            yield self._get_result(hit) 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def reindex(src_index, dst_index, type_list, chunk_size=None, time=None):
    """Reindex a set of indexes internally within ElasticSearch. All of the
       documents under the types that live in "type_list" under the index
       "src_index" will be copied into the documents under the same types
       in the index "dst_index". In other words, a perfect re-index!
       Instead of using the plugin API and consuming bandwidth to perform
       the re-index we will allow ElasticSearch to do some heavy lifting for
       us. Under the covers we are combining scan/scroll with bulk operations
       to do this re-indexing as efficient as possible.
    """
    es_engine = searchlight.elasticsearch.get_api()

    # Create a Query DSL string to access all documents within the specified
    # document types. We will filter on the "_type" field in this index. Since
    # there are multiple docuent types, we will need to use the "terms" filter.
    # All of the document types will be added to the list for "_type". We need
    # to enable version to allow the search to return the version field. This
    # will be used by the reindexer.
    body = {"version": "true",
            "query": {"bool": {"filter": {"terms": {"_type": type_list}}}}}
    # Debug: Show all documents that ES will re-index.
    # LOG.debug(es_engine.search(index=src_index, body=body, size=500))
    helper_reindex(client=es_engine, source_index=src_index,
                   target_index=dst_index, query=body) 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def scan_index(index: str, model: Model) -> Generator:
    """
    Yield all documents of model type in an index.

    This function calls the elasticsearch.helpers.scan function,
    and yields all the documents in the index that match the doc_type
    produced by a specific Django model.

    Args:
        index: string, the name of the index to scan, must be a configured
            index as returned from settings.get_index_names.
        model: a Django model type, used to filter the the documents that
            are scanned.

    Yields each document of type model in index, one at a time.

    """
    # noqa: E501, see https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-type-query.html
    query = {"query": {"type": {"value": model._meta.model_name}}}
    client = get_client()
    for hit in helpers.scan(client, index=index, query=query):
        yield hit 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def dump_documents(client, index, out_path, total_docs, progress_message_suffix=""):
    from elasticsearch import helpers

    logger = logging.getLogger(__name__)
    freq = max(1, total_docs // 1000)

    progress = console.progress()
    compressor = DOCS_COMPRESSOR()
    comp_outpath = out_path + COMP_EXT
    with open(out_path, "wb") as outfile:
        with open(comp_outpath, "wb") as comp_outfile:
            logger.info("Dumping corpus for index [%s] to [%s].", index, out_path)
            query = {"query": {"match_all": {}}}
            for n, doc in enumerate(helpers.scan(client, query=query, index=index)):
                if n > total_docs:
                    break
                data = (json.dumps(doc["_source"], separators=(",", ":")) + "\n").encode("utf-8")

                outfile.write(data)
                comp_outfile.write(compressor.compress(data))

                render_progress(progress, progress_message_suffix, index, n + 1, total_docs, freq)

            comp_outfile.write(compressor.flush())
    progress.finish() 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def read_item(self, from_date=None):
        """Read items one by one.

        :param from_date: start date for incremental reading
        :return: _source field of each ES hit.
        :raises ValueError: `metadata__timestamp` field not found in index
        :raises NotFoundError: index not found in ElasticSearch
        """

        search_query = self._build_search_query(from_date)
        for hit in helpers.scan(self._es_conn,
                                search_query,
                                scroll='300m',
                                index=self._es_index,
                                preserve_order=True):
            yield hit["_source"] 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def scan(self):
        """
        Turn the search into a scan search and return a generator that will
        iterate over all the documents matching the query.

        Use ``params`` method to specify any additional arguments you with to
        pass to the underlying ``scan`` helper from ``elasticsearch-py`` -
        https://elasticsearch-py.readthedocs.io/en/master/helpers.html#elasticsearch.helpers.scan

        """
        es = get_connection(self._using)

        for hit in scan(
                es,
                query=self.to_dict(),
                index=self._index,
                **self._params
        ):
            yield self._get_result(hit) 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def get_link_list(self, website_id, base_url):

        hits = helpers.scan(client=self.es,
                            query={
                                "_source": {
                                    "includes": ["path", "name", "ext"]
                                },
                                "query": {
                                    "constant_score": {
                                        "filter": {
                                            "term": {"website_id": website_id}
                                        }
                                    }
                                },
                            },
                            index=self.index_name, request_timeout=20, routing=website_id)
        for hit in hits:
            src = hit["_source"]
            yield urljoin(base_url, "/") + src["path"] + ("/" if src["path"] != "" else "") + src["name"] + \
                  ("." if src["ext"] != "" else "") + src["ext"] 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def clear(cls, index=None, using=None):
        """
        Deletes the Elasticsearch mapping associated with this document type.
        """
        using = using or cls._doc_type.using or 'default'
        index = index or cls._doc_type.index or getattr(settings, 'SEEKER_INDEX', 'seeker')
        es = connections.get_connection(using)
        if es.indices.exists_type(index=index, doc_type=cls._doc_type.name):
            def get_actions():
                for hit in scan(es, index=index, doc_type=cls._doc_type.name, query={'query': {'match_all': {}}}):
                    yield {
                        '_op_type': 'delete',
                        '_index': index,
                        '_type': cls._doc_type.name,
                        '_id': hit['_id'],
                    }
            bulk(es, get_actions())
            es.indices.refresh(index=index) 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def run_query(self):
        self.vprint("{info} Gathering flow data... this may take a while...".format(info=self.info))

        FLOW_BYTES = self.beacon_flow_bytes_toserver
        if self.suricata_defaults:
            FLOW_BYTES = 'flow.' + FLOW_BYTES

        query = self.hour_query(self.period, self.beacon_src_ip, self.beacon_dest_ip, self.beacon_destination_port,
                                self.beacon_timestamp, FLOW_BYTES, self.beacon_flow_id)
        self.dprint(query)
        resp = helpers.scan(query=query, client=self.es, scroll="90m", index=self.es_index, timeout="10m")
        df = pd.DataFrame([rec['_source'] for rec in resp])
        if len(df) == 0:
            raise Exception("Elasticsearch did not retrieve any data. Please ensure your settings are correct inside the config file.")

        self.dprint(df)
        df['dest_port'] = df[self.beacon_destination_port].fillna(0).astype(int)

        if 'flow' in df.columns:
            df[self.beacon_flow_bytes_toserver] = df['flow'].apply(lambda x: x.get(self.beacon_flow_bytes_toserver))

        df['triad_id'] = (df[self.beacon_src_ip] + df[self.beacon_dest_ip] + df[self.beacon_destination_port].astype(str)).apply(hash)
        df['triad_freq'] = df.groupby('triad_id')['triad_id'].transform('count').fillna(0).astype(int)
        self.high_freq = list(df[df.triad_freq > self.MIN_OCCURRENCES].groupby('triad_id').groups.keys())
        return df 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def delete(self, **kwargs):
        """
        Deletes a document from the index
        Pass an index and id to delete a specific document
        Pass a body with a query dsl to delete by query

        """

        kwargs = self._add_prefix(**kwargs)
        body = kwargs.pop("body", None)
        if body is not None:
            try:
                data = []
                refresh = kwargs.pop("refresh", False)
                for hit in helpers.scan(self.es, query=body, **kwargs):
                    hit["_op_type"] = "delete"
                    data.append(hit)

                return helpers.bulk(self.es, data, refresh=refresh, **kwargs)
            except Exception as detail:
                try:
                    # ignore 404 errors (index_not_found_exception)
                    if detail.status_code == 404:
                        pass
                except:
                    self.logger.warning(
                        "%s: WARNING: failed to delete document by query: %s \nException detail: %s\n" % (datetime.now(), body, detail)
                    )
                    raise detail
        else:
            try:
                return self.es.delete(ignore=[404], **kwargs)
            except Exception as detail:
                self.logger.warning("%s: WARNING: failed to delete document: %s \nException detail: %s\n" % (datetime.now(), body, detail))
                raise detail 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def get_all_doc(self, index, doc_type, search_body):
		results = helpers.scan(
								client=self.es,
								query=search_body,
								scroll="60s",
								index=index,
								doc_type=doc_type,
								timeout="60s")
		results_list = []
		for item in results:
			results_list.append(item["_source"])
		return results_list 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def _scan(self, index, search_range, bool_clause=None, sort_clause=None, query_fields=None, search_query=None,
              model_settings=None):
        """
        Scan and get documents in Elasticsearch

        :param index: on which index the request must be done
        :param search_range: the range of the search
        :param bool_clause: boolean condition
        :param sort_clause: request to sort results
        :param query_fields: the query field
        :param search_query: the search query
        :param model_settings: part of the configuration linked to the model
        :return: generator to fetch documents
        """
        preserve_order = False

        highlight_settings = self._get_highlight_settings(model_settings)

        if model_settings is not None and model_settings["process_documents_chronologically"]:
            sort_clause = {"sort": [{model_settings["timestamp_field"]: "desc"}]}
            preserve_order = True

        return eshelpers.scan(self.conn, request_timeout=self.settings.config.getint("general", "es_timeout"),
                              index=index, query=build_search_query(bool_clause=bool_clause,
                                                                    sort_clause=sort_clause,
                                                                    search_range=search_range,
                                                                    query_fields=query_fields,
                                                                    search_query=search_query,
                                                                    highlight_settings=highlight_settings),
                              size=self.settings.config.getint("general", "es_scan_size"),
                              scroll=self.settings.config.get("general", "es_scroll_time"),
                              preserve_order=preserve_order, raise_on_error=False) 

# 需要導入模塊: from elasticsearch import helpers [as 別名]
# 或者: from elasticsearch.helpers import scan [as 別名]
def scan(self, body, **kwargs):
        return scan(self.client, query=body, **kwargs)