def cluster_status(es):
cluster = ClusterClient(es)
print("\nCLUSTER HEALTH")
pprint(cluster.health())
print("\nPENDING TASKS")
pprint(cluster.pending_tasks())
print("\nNODES")
for node in get_nodes_info(es):
print(node.name, node.docs)
print("\nSHARD ALLOCATION")
cat = CatClient(es)
print(cat.allocation(v=True))
def cluster_status(es):
cluster = ClusterClient(es)
print "\nCLUSTER HEALTH"
pprint(cluster.health())
print "\nPENDING TASKS"
pprint(cluster.pending_tasks())
print "\nNODES"
for node in get_nodes_info(es):
print node.name, node.docs
print "\nSHARD ALLOCATION"
cat = CatClient(es)
print cat.allocation(v=True)
def __to_tf_idf(client, index, file_id):
def tf_idf(params):
(term, freq), (_, doc_freq) = params
tf = freq / max_freq
idf = np.log2(document_count / doc_freq)
return term, tf * idf
def document_term_vector():
tv = client.termvectors(index=index,
doc_type='document',
id=file_id,
fields=['text'],
positions=False,
term_statistics=True)
file_td, file_df = {}, {}
if 'text' in tv['term_vectors']:
for t in tv['term_vectors']['text']['terms']:
file_td[t] = tv['term_vectors']['text']['terms'][t][
'term_freq']
file_df[t] = tv['term_vectors']['text']['terms'][t][
'doc_freq']
return sorted(file_td.items()), sorted(file_df.items())
term_frequency, document_appearances = document_term_vector()
max_freq = max([f for _, f in term_frequency])
document_count = int(
CatClient(client).count(index=[index], format='json')[0]['count'])
vector = dict(map(tf_idf, zip(term_frequency, document_appearances)))
return Rocchio.__normalize(vector)
def doc_count(client, index):
"""
Returns the number of documents in an index
:param client:
:param index:
:return:
"""
return int(CatClient(client).count(index=[index], format='json')[0]['count'])
def doc_count(client, index):
"""
Returns the number of documents in an index
:param client: ElasticSearch client
:param index: Index to count documents from
:return: number of documents for desired index
"""
return int(
CatClient(client).count(index=[index], format='json')[0]['count'])
def relocate():
conf = config()
try:
es = Elasticsearch(conf['cluster_address'])
escat = CatClient(es)
escluster = ClusterClient(es)
except Exception, e:
print("Unable to connect to ES cluster. Reason: {}".format(e))
sys.exit(1)
def doc_count(client, index):
return int(CatClient(client).count(index=[index], format='json')[0]['count'])
def shard_status(es):
cat = CatClient(es)
print cat.shards(v=True)
from elasticsearch import Elasticsearch
from elasticsearch.client import IndicesClient
from elasticsearch.client import CatClient
import json
host = '192.168.15.168'
es = Elasticsearch(hosts=host)
print(es.ping())
index_cli = IndicesClient(es)
# print(index_cli)
cat_cli = CatClient(es)
all_index = cat_cli.indices()
# print(all_index)
# get all index name
index_list_source = all_index.split('\n')[:-1]
index_list = []
for i in index_list_source:
index = i.split()[2]
index_list.append(index)
# print(index_list)
# get index mapping info
for i in index_list:
mapping_info = index_cli.get_mapping(index=i)
mapping_info = json.dumps(mapping_info, indent=2, ensure_ascii=False)
print('============')
# print(i,mapping_info)
def shard_status(es):
cat = CatClient(es)
print(cat.shards(v=True))
from elasticsearch import Elasticsearch from elasticsearch.client import IndicesClient from elasticsearch.client import CatClient import json host = '127.0.0.1:9200' es = Elasticsearch(hosts=host) index_cli = IndicesClient(es) cat_cli = CatClient(es) index_list = cat_cli.indices() print(index_list) result = index_cli.get_settings(index="test_index0") # result = json.dumps(result,indent=2) print(result)