Python IndicesClient.get_mapping方法代码示例

# 需要导入模块: from elasticsearch.client import IndicesClient [as 别名]
# 或者: from elasticsearch.client.IndicesClient import get_mapping [as 别名]
def main():
    # Define the globals
    global index_names
    global STARTED_TIMESTAMP
    global es
    global es_indices
    try:
        # Initiate the elasticsearch session using ES low-level client.
        # By default nodes are randomized before passed into the pool and round-robin strategy is used for load balancing.
        es = Elasticsearch(ES_HOSTS, timeout=30)
        es_indices = IndicesClient(es)

    except:
        print("Could not connect to elasticsearch!")
        sys.exit(1)

    print("Creating indices.. \n"),
    indices = generate_indices()
    print("Done!\n")

    # Register specific mapping definition for a specific type.
    print("Put Mapping \n"),
    es_indices.put_mapping(doc_type="_default_", body=mappings_body["_default_"], index="_all" )
    for type_name in types:
        es_indices.put_mapping(doc_type=type_name, body=mappings_body[type_name], index="_all" )
    print("Done!\n")

    # Retrieve mapping definition of index or index/type.
    print("GET Mapping \n"),
    print json.dumps(es_indices.get_mapping(index=["metrics_0", "metrics_1"],
                     doc_type=types),
                     sort_keys=True,
                     indent=4,
                     separators=(',', ': '))
    #print json.dumps(es_indices.get_settings(index="_all"), sort_keys=True,indent=4, separators=(',', ': '))
    print("Done!\n")

    # We will Clean up the indices by default
    # Default: True
    if CLEANUP:
        print("Cleaning up created indices.. "),
        cleanup_indices()
        print("Done!\n")

# 需要导入模块: from elasticsearch.client import IndicesClient [as 别名]
# 或者: from elasticsearch.client.IndicesClient import get_mapping [as 别名]
lat_dist = maxlat - minlat
lon_dist = maxlon - minlon

spread = 0.085
distance_in_meters = 5000

if lat_dist < spread or lon_dist < spread:
  spread = 0.015
  distance_in_meters = 1000
  minlat = minlat + (0.01)
  maxlat = maxlat - (0.01)
  minlon = minlon + (0.01)
  maxlon = maxlon - (0.01)
realtime = True

if not ic.get_mapping(index="instagram_remap",doc_type=direct):
  body = ic.get_mapping(index="instagram_remap",doc_type="baltimore")["instagram_remap"]["mappings"]["baltimore"]
  ic.put_mapping(index="instagram_remap",doc_type=direct,body=body)


start_date = datetime(int(sdate[0:4]),int(sdate[4:6]),int(sdate[6:8]),int(sdate[8:10]))
end_date = datetime(datetime.now().year,datetime.now().month,datetime.now().day,datetime.now().hour,datetime.now().minute)
if args.end_date:
  end_date = datetime(int(args.end_date[0:4]),int(args.end_date[4:6]),int(args.end_date[6:8]),int(args.end_date[8:10]))

max_secs = 460800 # 128 hours

max_images = 40 # this is the artifical max limit instagram sets...for now we'll just make it something low
min_images = 10 # increase the time window for any calls netting less than 10 images

if args.images:

# 需要导入模块: from elasticsearch.client import IndicesClient [as 别名]
# 或者: from elasticsearch.client.IndicesClient import get_mapping [as 别名]
        print ("file not found")
        return
    actions=[]
    if not es.indices.exists(index=indexName,allow_no_indices=True):
        es.indices.create(index=indexName,body={},ignore=400)
    for item in csv.DictReader(open(fileName, 'r')):  
        actions.append({"_index":indexName,"_type":typeName,"_source":item})
    res = helpers.bulk(es,actions,chunk_size=100)
    es.indices.flush(index=[indexName])
    return len(actions)
result=importCSV("platform","facebook","demo_test.csv")
from elasticsearch import Elasticsearch
from elasticsearch.client import IndicesClient
es = Elasticsearch([{'host': 'localhost', 'port': 9200}])
es_index=IndicesClient(es)
es_index.get_mapping(index="platform",doc_type="facebook")
need_save = es.search(index='platform',doc_type='facebook', body={"query":{"match_phrase":{"_all":u"蔡英文"}},"sort":{u"留言數":{"order":"desc"}}})
es.count(index='platform',doc_type='facebook', body={"query":{"match_phrase":{"_all":u"蔡英文"}},"sort":{u"留言數":{"order":"desc"}}})
len(need_save['hits']['hits'])
import json
need_save = json.dumps(need_save['hits']['hits'],ensure_ascii=False).encode('utf8')
g = open('save_the_file.csv','wb+')
g.write(need_save)
g.close()
pd.read_csv('save_the_file.csv')
#打開看存檔
g = open('save_the_file.csv','r+')
y = json.load(g)
g.close()
print (y)
g = open('save_the_file.json','wb+')