class FullTextSearch(object):
def __init__(self, server, settings=None):
# These timeout and bulk_size parameters were determined through
# trial and error to be necessary to avoid timeout errors when
# generating indices on Sandbox. They should not be taken as gospel.
self.conn = ES(server, timeout=120.0) # Default timeout: 30.0
self.conn.bulker.bulk_size = 25 # Default: 400
if settings:
self.settings = settings
else:
self.settings = {
'index': {
'analysis': {
'analyzer': {
'ngram_analyzer': {
'tokenizer': 'keyword',
'filter': ['lowercase', 'filter_ngram'],
'type': 'custom'
}
},
'filter': {
'filter_ngram': {
'type': 'nGram',
'max_gram': 30,
'min_gram': 1
}
}
}
}
}
self.refresh_index_cache()
def search_index_text(self, query_string, fields="_all", **args):
q = query.MatchQuery(fields, query_string)
return self.search_index(q, **args)
def search_index(self, query, indices=None, num_results=None, node_type=None):
results = self.conn.search(
query=query, indices=indices, doc_types=node_type)
meta_list = [r.get_meta() for r in results[0:num_results]]
node_dict = {}
# fetch nodes grouped by type to reduce number of db calls
key = itemgetter('type')
for t, grouped_list in groupby(sorted(meta_list, key=key), key=key):
ids = [meta['id'] for meta in grouped_list]
for node in self.datastore.get_nodes(t, ids):
node_dict[(node.type, node.key)] = node
# return nodes in original order
nodelist = [node_dict[(meta['type'], meta['id'])]
for meta in meta_list]
return nodelist
def create_index(self, type, indexed_variables, index_name):
self.conn.indices.create_index_if_missing(index_name, self.settings)
mapping = {}
for arg in indexed_variables:
mapping[arg] = {'boost': 1.0,
'analyzer': 'ngram_analyzer',
'type': 'string',
'term_vector': 'with_positions_offsets'}
index_settings = {'index_analyzer': 'ngram_analyzer',
'search_analyzer': 'standard',
'properties': mapping}
self.conn.indices.put_mapping(str(type), index_settings, [index_name])
self.refresh_index_cache()
self.populate_index(type, index_name)
def refresh_index_cache(self):
try:
indices = self.conn.indices.get_mapping(raw=True)
except exceptions.IndexMissingException:
indices = {}
else:
indices = dict((k, v.get('mappings', {})) for k, v in indices.items())
self.indices = indices
def delete_index(self, index_name):
self.conn.indices.delete_index_if_exists(index_name)
self.refresh_index_cache()
def populate_index(self, type, index_name):
#add all the currently existing nodes into the index
ref_node = self.datastore.get_reference_node(type)
node_list = [rel.target_node for rel in ref_node.instance.outgoing]
for node in node_list:
key = node.key
index_dict = self.populate_index_document(node, index_name)
try:
self.conn.delete(index_name, type, key)
except ELASTIC_SEARCH_EXCEPTIONS as err:
log.exception(err)
pass
self.conn.index(index_dict, index_name, type, key, bulk=True)
self.conn.indices.refresh([index_name])
def on_create(self, node):
type_indices = self.get_indices_of_type(node.type)
for index_name in type_indices:
index_dict = self.populate_index_document(node, index_name)
try:
self.conn.index(index_dict, index_name, node.type, node.key, bulk=True)
self.conn.indices.refresh([index_name])
except ELASTIC_SEARCH_EXCEPTIONS as err:
log.exception(err)
pass
def on_delete(self, node):
type_indices = self.get_indices_of_type(node.type)
for index_name in type_indices:
try:
self.conn.delete(index_name, node.type, node.key, bulk=True)
self.conn.indices.refresh([index_name])
except ELASTIC_SEARCH_EXCEPTIONS as err:
log.exception(err)
pass
def on_modify(self, node):
type_indices = self.get_indices_of_type(node.type)
for index_name in type_indices:
index_dict = self.populate_index_document(node, index_name)
try:
self.conn.delete(index_name, node.type, node.key)
self.conn.index(index_dict, index_name, node.type, node.key, bulk=True)
self.conn.indices.refresh([index_name])
except ELASTIC_SEARCH_EXCEPTIONS as err:
log.exception(err)
pass
def get_indices_of_type(self, type):
type_indices = [
key for key, value in self.indices.items()
if type in value
]
return type_indices
def populate_index_document(self, node, index_name):
indexed_variables = self.indices[index_name][node.type]['properties'].keys()
index_dict = {
field: node[field] for field in indexed_variables
}
return index_dict
class FullTextSearch(object):
def __init__(self, server, settings=None):
self.conn = ES(server)
self.indices = {}
if settings:
self.settings = settings
else:
self.settings = {
'index': {
'analysis': {
'analyzer': {
'ngram_analyzer': {
'tokenizer': 'keyword',
'filter': ['lowercase', 'filter_ngram'],
'type': 'custom'
}
},
'filter': {
'filter_ngram': {
'type': 'nGram',
'max_gram': 30,
'min_gram': 1
}
}
}
}
}
def search_index(self, type, index_names, query_string, num_results=-1):
ns_index_names = [
str(type) + "-_-" + index_name for index_name in index_names
]
q = WildcardQuery('_all', lower(query_string))
results = self.conn.search(query=q,
indices=ns_index_names,
doc_types=type)
num_found = len(results)
if (num_results > num_found):
num_results = num_found
nodelist = [
self.datastore.get_node(type, r['_id'])
for r in results['hits']['hits']
]
if (num_results != -1):
return nodelist[0:num_results]
else:
return nodelist
def create_index(self, type, indexed_variables, index_name):
ns_index_name = str(type) + "-_-" + index_name
self.conn.delete_index_if_exists(ns_index_name)
self.conn.create_index(ns_index_name, self.settings)
mapping = {}
for arg in indexed_variables:
mapping[arg] = {
'boost': 1.0,
'analyzer': 'ngram_analyzer',
'type': u'string',
'term_vector': 'with_positions_offsets'
}
index_settings = {
'index_analyzer': 'ngram_analyzer',
'search_analyzer': 'standard',
'properties': mapping
}
self.conn.put_mapping(str(type), index_settings, [ns_index_name])
self.refresh_index_cache()
self.populate_index(type, index_name)
def refresh_index_cache(self):
self.indices = self.conn.get_indices()
def delete_index(self, type, index_name):
ns_index_name = str(type) + "-_-" + index_name
self.conn.delete_index_if_exists(ns_index_name)
self.refresh_index_cache()
def populate_index(self, type, index_name):
#add all the currently existing nodes into the index
ns_index_name = str(type) + "-_-" + index_name
ref_node = self.datastore.get_reference_node(type)
node_list = [rel.target_node for rel in ref_node.instance.outgoing]
mapping = self.conn.get_mapping(type, ns_index_name)
for node in node_list:
key = node.key
index_dict = self.populate_index_document(type, ns_index_name,
node.attributes, mapping)
try:
self.conn.delete(ns_index_name, type, key)
except exceptions.NotFoundException:
pass
try:
self.conn.index(index_dict, ns_index_name, type, key)
except exceptions.ElasticSearchParseException:
pass
self.conn.refresh([ns_index_name])
def on_create(self, node):
type_indices = self.get_indices_of_type(node.type)
for ns_index_name in type_indices:
mapping = self.conn.get_mapping(node.type, ns_index_name)
index_dict = self.populate_index_document(node.type, ns_index_name,
node.attributes, mapping)
self.conn.index(index_dict, ns_index_name, node.type, node.key)
self.conn.refresh([ns_index_name])
def on_delete(self, node):
type_indices = self.get_indices_of_type(node.type)
for ns_index_name in type_indices:
try:
self.conn.delete(ns_index_name, node.type, node.key)
self.conn.refresh([ns_index_name])
except exceptions.NotFoundException:
pass
def on_modify(self, node):
type_indices = self.get_indices_of_type(node.type)
for ns_index_name in type_indices:
mapping = self.conn.get_mapping(node.type, ns_index_name)
index_dict = self.populate_index_document(node.type, ns_index_name,
node.attributes, mapping)
try:
self.conn.delete(ns_index_name, node.type, node.key)
self.conn.index(index_dict, ns_index_name, node.type, node.key)
self.conn.refresh([ns_index_name])
except exceptions.NotFoundException:
pass
def get_indices_of_type(self, type):
type_indices = []
for index in self.indices.keys():
if index.startswith(type + "-_-"):
type_indices.append(index)
return type_indices
def populate_index_document(self, type, ns_index_name, attributes,
mapping):
indexed_variables = mapping[type]['properties'].keys()
index_dict = {}
for arg in indexed_variables:
try:
index_dict[arg] = attributes[arg]
except KeyError:
#if this attribute doesn't exist for this node, just pass
pass
return index_dict
class FullTextSearch(object):
def __init__(self,server,settings = None ):
self.conn = ES(server)
self.indices = {}
if settings:
self.settings = settings
else:
self.settings = {
'index': {
'analysis' : {
'analyzer' : {
'ngram_analyzer' : {
'tokenizer' : 'keyword',
'filter' : ['lowercase', 'filter_ngram'],
'type' : 'custom'
}
},
'filter' : {
'filter_ngram' : {
'type' : 'nGram',
'max_gram' : 30,
'min_gram' : 1
}
}
}
}
}
def search_index(self, type, index_names, query_string, num_results=-1):
ns_index_names= [str(type) + "-_-" + index_name for index_name in index_names]
q = WildcardQuery('_all',lower(query_string))
results = self.conn.search(query=q, indices=ns_index_names, doc_types=type)
num_found = len(results)
if(num_results > num_found):
num_results = num_found
nodelist = [self.datastore.get_node(type,r['_id']) for r in results['hits']['hits']]
if(num_results!=-1):
return nodelist[0:num_results]
else:
return nodelist
def create_index(self, type, indexed_variables, index_name):
ns_index_name = str(type) + "-_-" + index_name
self.conn.delete_index_if_exists(ns_index_name)
self.conn.create_index(ns_index_name,self.settings)
mapping = {}
for arg in indexed_variables:
mapping[arg] = {'boost':1.0,
'analyzer' : 'ngram_analyzer',
'type': u'string',
'term_vector': 'with_positions_offsets'}
index_settings = {'index_analyzer':'ngram_analyzer',
'search_analyzer':'standard',
'properties':mapping}
self.conn.put_mapping(str(type),index_settings,[ns_index_name])
self.refresh_index_cache()
self.populate_index(type, index_name)
def refresh_index_cache(self):
self.indices = self.conn.get_indices()
def delete_index(self,type,index_name):
ns_index_name = str(type) + "-_-" + index_name
self.conn.delete_index_if_exists(ns_index_name)
self.refresh_index_cache()
def populate_index(self, type, index_name):
#add all the currently existing nodes into the index
ns_index_name = str(type) + "-_-" + index_name
ref_node = self.datastore.get_reference_node(type)
node_list = [rel.target_node for rel in ref_node.instance.outgoing]
mapping = self.conn.get_mapping(type,ns_index_name)
for node in node_list:
key = node.key
index_dict = self.populate_index_document(type,ns_index_name,node.attributes,mapping)
try:
self.conn.delete(ns_index_name,type,key)
except exceptions.NotFoundException:
pass
try:
self.conn.index(index_dict,ns_index_name,type,key)
except exceptions.ElasticSearchParseException:
pass
self.conn.refresh([ns_index_name])
def on_create(self,node):
type_indices = self.get_indices_of_type(node.type)
for ns_index_name in type_indices:
mapping = self.conn.get_mapping(node.type,ns_index_name)
index_dict = self.populate_index_document(node.type,ns_index_name,node.attributes,mapping)
self.conn.index(index_dict,ns_index_name,node.type,node.key)
self.conn.refresh([ns_index_name])
def on_delete(self, node):
type_indices = self.get_indices_of_type(node.type)
for ns_index_name in type_indices:
try:
self.conn.delete(ns_index_name,node.type,node.key)
self.conn.refresh([ns_index_name])
except exceptions.NotFoundException:
pass
def on_modify(self, node):
type_indices = self.get_indices_of_type(node.type)
for ns_index_name in type_indices:
mapping = self.conn.get_mapping(node.type,ns_index_name)
index_dict = self.populate_index_document(node.type,ns_index_name,node.attributes,mapping)
try:
self.conn.delete(ns_index_name,node.type,node.key)
self.conn.index(index_dict,ns_index_name,node.type,node.key)
self.conn.refresh([ns_index_name])
except exceptions.NotFoundException:
pass
def get_indices_of_type(self,type):
type_indices = []
for index in self.indices.keys():
if index.startswith(type+"-_-"):
type_indices.append(index)
return type_indices
def populate_index_document(self,type,ns_index_name,attributes,mapping):
indexed_variables = mapping[type]['properties'].keys()
index_dict = {}
for arg in indexed_variables:
try:
index_dict[arg] = attributes[arg]
except KeyError:
#if this attribute doesn't exist for this node, just pass
pass
return index_dict
class FullTextSearch(object):
def __init__(self, server, settings=None):
self.conn = ES(server)
if settings:
self.settings = settings
else:
self.settings = {
'index': {
'analysis': {
'analyzer': {
'ngram_analyzer': {
'tokenizer': 'keyword',
'filter': ['lowercase', 'filter_ngram'],
'type': 'custom'
}
},
'filter': {
'filter_ngram': {
'type': 'nGram',
'max_gram': 30,
'min_gram': 1
}
}
}
}
}
self.refresh_index_cache()
def search_index_text(self, query_string, fields="_all", **args):
q = query.TextQuery(fields, query_string)
return self.search_index(q, **args)
def search_index(self, query, indices=None, num_results=None, node_type=None):
results = self.conn.search(
query=query, indices=indices, doc_types=node_type)
meta_list = [r.get_meta() for r in results[0:num_results]]
node_dict = {}
# fetch nodes grouped by type to reduce number of db calls
key = itemgetter('type')
for t, grouped_list in groupby(sorted(meta_list, key=key), key=key):
ids = [meta['id'] for meta in grouped_list]
for node in self.datastore.get_nodes(t, ids):
node_dict[(node.type, node.key)] = node
# return nodes in original order
nodelist = [node_dict[(meta['type'], meta['id'])]
for meta in meta_list]
return nodelist
def create_index(self, type, indexed_variables, index_name):
self.conn.create_index_if_missing(index_name, self.settings)
mapping = {}
for arg in indexed_variables:
mapping[arg] = {'boost': 1.0,
'analyzer': 'ngram_analyzer',
'type': 'string',
'term_vector': 'with_positions_offsets'}
index_settings = {'index_analyzer': 'ngram_analyzer',
'search_analyzer': 'standard',
'properties': mapping}
self.conn.put_mapping(str(type), index_settings, [index_name])
self.refresh_index_cache()
self.populate_index(type, index_name)
def refresh_index_cache(self):
try:
self.indices = self.conn.get_mapping()
except exceptions.IndexMissingException:
self.indices = {}
def delete_index(self, index_name):
self.conn.delete_index_if_exists(index_name)
self.refresh_index_cache()
def populate_index(self, type, index_name):
#add all the currently existing nodes into the index
ref_node = self.datastore.get_reference_node(type)
node_list = [rel.target_node for rel in ref_node.instance.outgoing]
for node in node_list:
key = node.key
index_dict = self.populate_index_document(node, index_name)
try:
self.conn.delete(index_name, type, key)
except exceptions.NotFoundException:
pass
self.conn.index(index_dict, index_name, type, key)
self.conn.refresh([index_name])
def on_create(self, node):
type_indices = self.get_indices_of_type(node.type)
for index_name in type_indices:
index_dict = self.populate_index_document(node, index_name)
self.conn.index(index_dict, index_name, node.type, node.key)
self.conn.refresh([index_name])
def on_delete(self, node):
type_indices = self.get_indices_of_type(node.type)
for index_name in type_indices:
try:
self.conn.delete(index_name, node.type, node.key)
self.conn.refresh([index_name])
except exceptions.NotFoundException:
pass
def on_modify(self, node):
type_indices = self.get_indices_of_type(node.type)
for index_name in type_indices:
index_dict = self.populate_index_document(node, index_name)
try:
self.conn.delete(index_name, node.type, node.key)
self.conn.index(index_dict, index_name, node.type, node.key)
self.conn.refresh([index_name])
except exceptions.NotFoundException:
pass
def get_indices_of_type(self, type):
type_indices = [
key for key, value in self.indices.items()
if type in value
]
return type_indices
def populate_index_document(self, node, index_name):
indexed_variables = self.indices[index_name][node.type]['properties'].keys()
index_dict = {
field: node[field] for field in indexed_variables
}
return index_dict
