def _run(self):
json_dir = self.input()['data'].path
mapper = LoadJSONMapper(config.es_host(),
index_name=self.index_name,
type_name=self.type_name,
docid_key=self.docid_key,
incremental=self.use_checksum)
parallel.mapreduce(parallel.Collection.from_sharded(json_dir),
mapper=mapper,
reducer=parallel.IdentityReducer(),
output_format=parallel.NullOutput(),
map_workers=self.load_json_workers,
num_shards=1,
output_prefix=config.tmp_dir('%s/load-json' %
self.index_name))
# update metadata index
elasticsearch_requests.update_process_datetime(
config.es_client(), self.index_name,
arrow.utcnow().format('YYYY-MM-DD'))
# optimize index, if requested
if self.optimize_index:
optimize_index(self.index_name, wait_for_merge=False)
# update metadata index again. Trying to solve mystery of missing "last_update_date" entries...
elasticsearch_requests.update_process_datetime(
config.es_client(), self.index_name,
arrow.utcnow().format('YYYY-MM-DD'))
def _run(self):
logging.info('Optimizing %s', self.index_name)
es = config.es_client()
es.indices.optimize(
index=self.index_name,
max_num_segments=1
)
def _run(self):
json_data = json.load(open(self.input()['data'].path))
date_str = basename(dirname(dirname(self.input()['data'].path)))
index_dict = {
'index': self.index_name,
'doc_type': self.type_name,
'id': date_str,
'body': json_data
}
es_client = elasticsearch.Elasticsearch(config.es_host(), timeout=60)
# We put the same document into the index twice.
# Once with a key as its date
# Once with a key of `current`
# The API will serve the current key as its default response.
# How we serve archive records is TBD, but the data is preserved this way.
es_client.index(**index_dict)
index_dict['id'] = 'current'
es_client.index(**index_dict)
elasticsearch_requests.update_process_datetime(
config.es_client(), self.index_name,
arrow.utcnow().format('YYYY-MM-DD'),
arrow.utcnow().format('YYYY-MM-DD'))
def _run(self):
json_dir = self.input()['data'].path
mapper = LoadJSONMapper(
config.es_host(),
index_name=self.index_name,
type_name=self.type_name,
docid_key=self.docid_key,
incremental=self.use_checksum
)
parallel.mapreduce(
parallel.Collection.from_sharded(json_dir),
mapper=mapper,
reducer=parallel.IdentityReducer(),
output_format=parallel.NullOutput(),
map_workers=self.load_json_workers,
num_shards=1,
output_prefix=config.tmp_dir('%s/load-json' % self.index_name)
)
# update metadata index
elasticsearch_requests.update_process_datetime(
config.es_client(), self.index_name, arrow.utcnow().format('YYYY-MM-DD')
)
# optimize index, if requested
if self.optimize_index:
optimize_index(self.index_name, wait_for_merge=False)
def _run(self):
json_dir = self.input()['data'].path
mapper = LoadJSONMapper(config.es_host(),
index_name=self.index_name,
type_name=self.type_name,
docid_key=self.docid_key,
incremental=self.use_checksum)
parallel.mapreduce(parallel.Collection.from_sharded(json_dir),
mapper=mapper,
reducer=parallel.IdentityReducer(),
output_format=parallel.NullOutput(),
map_workers=self.load_json_workers,
num_shards=1,
output_prefix=config.tmp_dir('%s/load-json' %
self.index_name))
# update metadata index
elasticsearch_requests.update_process_datetime(
config.es_client(),
self.index_name,
last_run_date=arrow.utcnow().format('YYYY-MM-DD'),
last_update_date=self.last_update_date()
if callable(self.last_update_date) else self.last_update_date)
# Refresh the index to make the documents visible to searches.
refresh_index(self.index_name)
# optimize index, if requested
if self.optimize_index:
optimize_index(self.index_name, wait_for_merge=False)
def _run(self):
json_dir = self.input()['data'].path
mapper = LoadJSONMapper(config.es_host(),
index_name=self.index_name,
type_name=self.type_name,
docid_key=self.docid_key,
incremental=self.use_checksum)
parallel.mapreduce(parallel.Collection.from_sharded(json_dir),
mapper=mapper,
reducer=parallel.IdentityReducer(),
output_format=parallel.NullOutput(),
map_workers=self.load_json_workers,
output_prefix=config.tmp_dir('%s/load-json' %
self.index_name))
# update metadata index
elasticsearch_requests.update_process_datetime(
config.es_client(), self.index_name,
arrow.utcnow().format('YYYY-MM-DD'))
def _run(self):
json_data = json.load(open(self.input()['data'].path))
date_str = basename(dirname(dirname(self.input()['data'].path)))
index_dict = {
'index': self.index_name,
'doc_type': self.type_name,
'id': date_str,
'body': json_data
}
es_client = elasticsearch.Elasticsearch(config.es_host())
# We put the same document into the index twice.
# Once with a key as its date
# Once with a key of `current`
# The API will serve the current key as its default response.
# How we serve archive records is TBD, but the data is preserved this way.
es_client.index(**index_dict)
index_dict['id'] = 'current'
es_client.index(**index_dict)
elasticsearch_requests.update_process_datetime(
config.es_client(), self.index_name, arrow.utcnow().format('YYYY-MM-DD')
)
def _run(self):
logging.info('Optimizing %s', self.index_name)
es = config.es_client()
es.indices.optimize(index=self.index_name, max_num_segments=1)