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# Licensed to Elasticsearch B.V. under one or more contributor
# license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright
# ownership. Elasticsearch B.V. licenses this file to you under
# the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import os
from typing import Any, Dict, Iterator, Mapping, Sequence, cast
from elasticsearch.dsl import Agg, Response, Search, aggs, connections
from elasticsearch.dsl.types import CompositeAggregate
from elasticsearch.helpers import bulk
from test_elasticsearch.test_dsl.test_integration.test_data import DATA, GIT_INDEX
def scan_aggs(
search: Search,
source_aggs: Sequence[Mapping[str, Agg]],
inner_aggs: Dict[str, Agg] = {},
size: int = 10,
) -> Iterator[CompositeAggregate]:
"""
Helper function used to iterate over all possible bucket combinations of
``source_aggs``, returning results of ``inner_aggs`` for each. Uses the
``composite`` aggregation under the hood to perform this.
"""
def run_search(**kwargs: Any) -> Response:
s = search[:0]
bucket = s.aggs.bucket(
"comp",
aggs.Composite(
sources=source_aggs,
size=size,
**kwargs,
),
)
for agg_name, agg in inner_aggs.items():
bucket[agg_name] = agg
return s.execute()
response = run_search()
while response.aggregations["comp"].buckets:
for b in response.aggregations["comp"].buckets:
yield cast(CompositeAggregate, b)
if "after_key" in response.aggregations["comp"]:
after = response.aggregations["comp"].after_key
else:
after = response.aggregations["comp"].buckets[-1].key
response = run_search(after=after)
def main() -> None:
# initiate the default connection to elasticsearch
client = connections.create_connection(hosts=[os.environ["ELASTICSEARCH_URL"]])
# create the index and populate it with some data
# note that the dataset is imported from the library's test suite
client.indices.delete(index="git", ignore_unavailable=True)
client.indices.create(index="git", **GIT_INDEX)
bulk(client, DATA, raise_on_error=True, refresh=True)
# run some aggregations on the data
for b in scan_aggs(
Search(index="git"),
[{"files": aggs.Terms(field="files")}],
{"first_seen": aggs.Min(field="committed_date")},
):
print(
"File %s has been modified %d times, first seen at %s."
% (b.key.files, b.doc_count, b.first_seen.value_as_string)
)
# close the connection
connections.get_connection().close()
if __name__ == "__main__":
main()
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