def index_resources_by_type(resource_types, clear_index=True, index_name=None, batch_size=settings.BULK_IMPORT_BATCH_SIZE):
"""
Indexes all resources of a given type(s)
Arguments:
resource_types -- array of graph ids that represent resource types
Keyword Arguments:
clear_index -- set to True to remove all the resources of the types passed in from the index before the reindexing operation
index_name -- only applies to custom indexes and if given will try and just refresh the data in that index
batch_size -- the number of records to index as a group, the larger the number to more memory required
"""
status = ''
se = SearchEngineFactory().create()
datatype_factory = DataTypeFactory()
node_datatypes = {str(nodeid): datatype for nodeid, datatype in models.Node.objects.values_list('nodeid', 'datatype')}
status = ''
for resource_type in resource_types:
start = datetime.now()
resources = Resource.objects.filter(graph_id=str(resource_type))
graph_name = models.GraphModel.objects.get(graphid=str(resource_type)).name
print("Indexing resource type '{0}'".format(graph_name))
if index_name is None:
q = Query(se=se)
term = Term(field='graph_id', term=str(resource_type))
q.add_query(term)
if clear_index:
q.delete(index='resources', refresh=True)
with se.BulkIndexer(batch_size=batch_size, refresh=True) as doc_indexer:
with se.BulkIndexer(batch_size=batch_size, refresh=True) as term_indexer:
for resource in resources:
document, terms = resource.get_documents_to_index(fetchTiles=True, datatype_factory=datatype_factory, node_datatypes=node_datatypes)
doc_indexer.add(index='resources', id=document['resourceinstanceid'], data=document)
for term in terms:
term_indexer.add(index='terms', id=term['_id'], data=term['_source'])
result_summary = {'database': len(resources), 'indexed': se.count(index='resources', body=q.dsl)}
status = 'Passed' if result_summary['database'] == result_summary['indexed'] else 'Failed'
print("Status: {0}, Resource Type: {1}, In Database: {2}, Indexed: {3}, Took: {4} seconds".format(status, graph_name, result_summary['database'], result_summary['indexed'], (datetime.now()-start).seconds))
for index in settings.ELASTICSEARCH_CUSTOM_INDEXES:
es_index = import_class_from_string(index['module'])(index['name'])
es_index.bulk_index(resources=resources, resource_type=resource_type, graph_name=graph_name, clear_index=clear_index)
else:
es_index = get_index(index_name)
es_index.bulk_index(resources=resources, resource_type=resource_type, graph_name=graph_name, clear_index=clear_index)
return status
def test_bulk_indexer(self):
se = SearchEngineFactory().create()
se.create_index(index="bulk")
with se.BulkIndexer(batch_size=500, refresh=True) as bulk_indexer:
for i in range(1001):
doc = {"id": i, "type": "prefLabel", "value": "test pref label"}
bulk_indexer.add(index="bulk", id=doc["id"], data=doc)
count_after = se.count(index="bulk")
self.assertEqual(count_after, 1001)
def index_resource_relations(clear_index=True,
batch_size=settings.BULK_IMPORT_BATCH_SIZE):
"""
Indexes all resource to resource relation records
Keyword Arguments:
clear_index -- set to True to remove all the resources from the index before the reindexing operation
batch_size -- the number of records to index as a group, the larger the number to more memory required
"""
start = datetime.now()
print("Indexing resource to resource relations")
cursor = connection.cursor()
se = SearchEngineFactory().create()
if clear_index:
q = Query(se=se)
q.delete(index="resource_relations")
with se.BulkIndexer(batch_size=batch_size,
refresh=True) as resource_relations_indexer:
sql = """
SELECT resourcexid, notes, datestarted, dateended, relationshiptype, resourceinstanceidfrom,
resourceinstanceidto, modified, created, inverserelationshiptype, tileid, nodeid
FROM public.resource_x_resource;
"""
cursor.execute(sql)
for resource_relation in cursor.fetchall():
doc = {
"resourcexid": resource_relation[0],
"notes": resource_relation[1],
"datestarted": resource_relation[2],
"dateended": resource_relation[3],
"relationshiptype": resource_relation[4],
"resourceinstanceidfrom": resource_relation[5],
"resourceinstanceidto": resource_relation[6],
"modified": resource_relation[7],
"created": resource_relation[8],
"inverserelationshiptype": resource_relation[9],
"tileid": resource_relation[10],
"nodeid": resource_relation[11],
}
resource_relations_indexer.add(index="resource_relations",
id=doc["resourcexid"],
data=doc)
index_count = se.count(index="resource_relations")
print("Status: {0}, In Database: {1}, Indexed: {2}, Took: {3} seconds".
format("Passed" if cursor.rowcount == index_count else "Failed",
cursor.rowcount, index_count,
(datetime.now() - start).seconds))
def test_bulk_indexer(self):
se = SearchEngineFactory().create()
se.create_index(index='bulk')
with se.BulkIndexer(batch_size=500, refresh=True) as bulk_indexer:
for i in range(1001):
doc = {
'id': i,
'type': 'prefLabel',
'value': 'test pref label',
}
bulk_indexer.add(index='bulk', id=doc['id'], data=doc)
count_after = se.count(index='bulk')
self.assertEqual(count_after, 1001)
def index_resource_relations(clear_index=True,
batch_size=settings.BULK_IMPORT_BATCH_SIZE):
"""
Indexes all resource to resource relation records
Keyword Arguments:
clear_index -- set to True to remove all the resources from the index before the reindexing operation
batch_size -- the number of records to index as a group, the larger the number to more memory required
"""
start = datetime.now()
print "Indexing resource to resource relations"
se = SearchEngineFactory().create()
if clear_index:
q = Query(se=se)
q.delete(index='resource_relations')
with se.BulkIndexer(batch_size=batch_size,
refresh=True) as resource_relations_indexer:
sql = """
SELECT resourcexid, resourceinstanceidfrom, notes, relationshiptype, resourceinstanceidto
FROM public.resource_x_resource;
"""
cursor = connection.cursor()
cursor.execute(sql)
for resource_relation in cursor.fetchall():
doc = {
'resourcexid': resource_relation[0],
'resourceinstanceidfrom': resource_relation[1],
'notes': resource_relation[2],
'relationshiptype': resource_relation[3],
'resourceinstanceidto': resource_relation[4]
}
resource_relations_indexer.add(index='resource_relations',
doc_type='all',
id=doc['resourcexid'],
data=doc)
index_count = se.es.count(index='resource_relations')['count']
print "Status: {0}, In Database: {1}, Indexed: {2}, Took: {3} seconds".format(
'Passed' if cursor.rowcount == index_count else 'Failed',
cursor.rowcount, index_count, (datetime.now() - start).seconds)
def index_concepts(clear_index=True,
batch_size=settings.BULK_IMPORT_BATCH_SIZE):
"""
Indxes all concepts from the database
Keyword Arguments:
clear_index -- set to True to remove all the concepts from the index before the reindexing operation
batch_size -- the number of records to index as a group, the larger the number to more memory required
"""
start = datetime.now()
print("Indexing concepts")
cursor = connection.cursor()
se = SearchEngineFactory().create()
if clear_index:
q = Query(se=se)
q.delete(index="concepts")
with se.BulkIndexer(batch_size=batch_size,
refresh=True) as concept_indexer:
indexed_values = []
for conceptValue in models.Value.objects.filter(
Q(concept__nodetype="Collection")
| Q(concept__nodetype="ConceptScheme"),
valuetype__category="label"):
doc = {
"category": "label",
"conceptid": conceptValue.concept_id,
"language": conceptValue.language_id,
"value": conceptValue.value,
"type": conceptValue.valuetype_id,
"id": conceptValue.valueid,
"top_concept": conceptValue.concept_id,
}
concept_indexer.add(index="concepts", id=doc["id"], data=doc)
indexed_values.append(doc["id"])
valueTypes = []
for valuetype in models.DValueType.objects.filter(
category="label").values_list("valuetype", flat=True):
valueTypes.append("'%s'" % valuetype)
valueTypes = ",".join(valueTypes)
for conceptValue in models.Relation.objects.filter(
relationtype="hasTopConcept"):
topConcept = conceptValue.conceptto_id
sql = """
WITH RECURSIVE children_inclusive AS (
SELECT d.conceptidfrom, d.conceptidto, c.*, 1 AS depth ---|NonRecursive Part
FROM relations d
JOIN values c ON(c.conceptid = d.conceptidto)
JOIN values c2 ON(c2.conceptid = d.conceptidfrom)
WHERE d.conceptidto = '{0}'
and c2.valuetype = 'prefLabel'
and c.valuetype in ({1})
and (d.relationtype = 'narrower' or d.relationtype = 'hasTopConcept')
UNION
SELECT d.conceptidfrom, d.conceptidto, v.*, depth+1 ---|RecursivePart
FROM relations d
JOIN children_inclusive b ON(b.conceptidto = d.conceptidfrom)
JOIN values v ON(v.conceptid = d.conceptidto)
JOIN values v2 ON(v2.conceptid = d.conceptidfrom)
WHERE v2.valuetype = 'prefLabel'
and v.valuetype in ({1})
and (d.relationtype = 'narrower' or d.relationtype = 'hasTopConcept')
) SELECT valueid, value, conceptid, languageid, valuetype FROM children_inclusive ORDER BY depth;
""".format(topConcept, valueTypes)
cursor.execute(sql)
for conceptValue in cursor.fetchall():
doc = {
"category": "label",
"conceptid": conceptValue[2],
"language": conceptValue[3],
"value": conceptValue[1],
"type": conceptValue[4],
"id": conceptValue[0],
"top_concept": topConcept,
}
concept_indexer.add(index="concepts", id=doc["id"], data=doc)
indexed_values.append(doc["id"])
# we add this step to catch any concepts/values that are orphaned (have no parent concept)
for conceptValue in models.Value.objects.filter(
valuetype__category="label").exclude(
valueid__in=indexed_values):
doc = {
"category": "label",
"conceptid": conceptValue.concept_id,
"language": conceptValue.language_id,
"value": conceptValue.value,
"type": conceptValue.valuetype_id,
"id": conceptValue.valueid,
"top_concept": conceptValue.concept_id,
}
concept_indexer.add(index="concepts", id=doc["id"], data=doc)
cursor.execute(
"SELECT count(*) from values WHERE valuetype in ({0})".format(
valueTypes))
concept_count_in_db = cursor.fetchone()[0]
index_count = se.count(index="concepts")
print("Status: {0}, In Database: {1}, Indexed: {2}, Took: {3} seconds".
format("Passed" if concept_count_in_db == index_count else "Failed",
concept_count_in_db, index_count,
(datetime.now() - start).seconds))
def index_concepts(clear_index=True, batch_size=settings.BULK_IMPORT_BATCH_SIZE):
"""
Indxes all concepts from the database
Keyword Arguments:
clear_index -- set to True to remove all the concepts from the index before the reindexing operation
batch_size -- the number of records to index as a group, the larger the number to more memory required
"""
start = datetime.now()
print "Indexing concepts"
cursor = connection.cursor()
se = SearchEngineFactory().create()
if clear_index:
q = Query(se=se)
q.delete(index='concepts')
with se.BulkIndexer(batch_size=batch_size, refresh=True) as concept_indexer:
concept_strings = []
for conceptValue in models.Value.objects.filter(Q(concept__nodetype='Collection') | Q(concept__nodetype='ConceptScheme'), valuetype__category='label'):
doc = {
'category': 'label',
'conceptid': conceptValue.concept_id,
'language': conceptValue.language_id,
'value': conceptValue.value,
'type': conceptValue.valuetype_id,
'id': conceptValue.valueid,
'top_concept': conceptValue.concept_id
}
concept_indexer.add(index='concepts', id=doc['id'], data=doc)
valueTypes = []
valueTypes2 = []
for valuetype in models.DValueType.objects.filter(category='label').values_list('valuetype', flat=True):
valueTypes2.append("%s" % valuetype)
valueTypes.append("'%s'" % valuetype)
valueTypes = ",".join(valueTypes)
for conceptValue in models.Relation.objects.filter(relationtype='hasTopConcept'):
topConcept = conceptValue.conceptto_id
sql = """
WITH RECURSIVE children_inclusive AS (
SELECT d.conceptidfrom, d.conceptidto, c.*, 1 AS depth ---|NonRecursive Part
FROM relations d
JOIN values c ON(c.conceptid = d.conceptidto)
JOIN values c2 ON(c2.conceptid = d.conceptidfrom)
WHERE d.conceptidto = '{0}'
and c2.valuetype = 'prefLabel'
and c.valuetype in ({1})
and (d.relationtype = 'narrower' or d.relationtype = 'hasTopConcept')
UNION
SELECT d.conceptidfrom, d.conceptidto, v.*, depth+1 ---|RecursivePart
FROM relations d
JOIN children_inclusive b ON(b.conceptidto = d.conceptidfrom)
JOIN values v ON(v.conceptid = d.conceptidto)
JOIN values v2 ON(v2.conceptid = d.conceptidfrom)
WHERE v2.valuetype = 'prefLabel'
and v.valuetype in ({1})
and (d.relationtype = 'narrower' or d.relationtype = 'hasTopConcept')
) SELECT valueid, value, conceptid, languageid, valuetype FROM children_inclusive ORDER BY depth;
""".format(topConcept, valueTypes)
cursor.execute(sql)
for conceptValue in cursor.fetchall():
doc = {
'category': 'label',
'conceptid': conceptValue[2],
'language': conceptValue[3],
'value': conceptValue[1],
'type': conceptValue[4],
'id': conceptValue[0],
'top_concept': topConcept
}
concept_indexer.add(index='concepts', id=doc['id'], data=doc)
cursor.execute("SELECT count(*) from values WHERE valuetype in ({0})".format(valueTypes))
concept_count_in_db = cursor.fetchone()[0]
index_count = se.count(index='concepts')
print "Status: {0}, In Database: {1}, Indexed: {2}, Took: {3} seconds".format('Passed' if concept_count_in_db == index_count else 'Failed', concept_count_in_db, index_count, (datetime.now()-start).seconds)
class BaseIndex(object):
def __init__(self, index_name=None):
if index_name is None or index_name == "":
raise SearchIndexError("Index name is not defined")
self.se = SearchEngineFactory().create()
self.index_metadata = None
self.index_name = index_name
def prepare_index(self):
"""
Defines the Elastic Search mapping and settings for an index
Arguments:
None
Keyword Arguments:
None
Return: None
"""
if self.index_metadata is not None:
self.se.create_index(index=self.index_name, body=self.index_metadata)
else:
raise SearchIndexError("No index metadata defined.")
def get_documents_to_index(self, resourceinstance, tiles):
"""
Gets a document to index into Elastic Search
Arguments:
resourceinstance -- resource instance object
tiles -- list of tiles that make up the resource instance
Keyword Arguments:
None
Return: tuple of (document, document id)
"""
raise NotImplementedError
def index_document(self, document=None, id=None):
"""
Indexes a document into Elastic Search
Arguments:
None
Keyword Arguments:
document -- the document to index
id -- the id of the document
Return: None
"""
if document is not None and id is not None:
self.se.index_data(index=self.index_name, body=document, id=id)
def index_resources(self, resources=None, batch_size=settings.BULK_IMPORT_BATCH_SIZE, quiet=False):
"""
Indexes a list of resources in bulk to Elastic Search
Keyword Arguments:
resources -- the list of resource instances to index
batch_size -- the number of records to index as a group, the larger the number to more memory required
quiet -- Silences the status bar output during certain operations, use in celery operations for example
Return: None
"""
start = datetime.now()
q = Query(se=self.se)
self.se.refresh(index=self.index_name)
count_before = self.se.count(index=self.index_name, body=q.dsl)
result_summary = {"database": len(resources), "indexed": 0}
if quiet is False:
bar = pyprind.ProgBar(len(resources), bar_char="█") if len(resources) > 1 else None
with self.se.BulkIndexer(batch_size=batch_size, refresh=True) as indexer:
for resource in resources:
if quiet is False and bar is not None:
bar.update(item_id=resource)
tiles = list(models.TileModel.objects.filter(resourceinstance=resource))
document, doc_id = self.get_documents_to_index(resource, tiles)
if document is not None and id is not None:
indexer.add(index=self.index_name, id=doc_id, data=document)
self.se.refresh(index=self.index_name)
result_summary["indexed"] = self.se.count(index=self.index_name, body=q.dsl) - count_before
status = "Passed" if result_summary["database"] == result_summary["indexed"] else "Failed"
print(f"Custom Index - {settings.ELASTICSEARCH_PREFIX}_{self.index_name}")
print(
f" Status: {status}, In Database: {result_summary['database']}, Indexed: {result_summary['indexed']}, Took: {(datetime.now() - start).seconds} seconds"
)
def delete_resources(self, resources=None):
"""
Deletes documents from an index based on the passed in list of resources
Delete by query, so this is a single operation
Keyword Arguments:
resources -- a single resource instance or a list of resource instances
"""
q = Query(se=self.se)
if not isinstance(resources, list):
resourcelist = [resources]
else:
resourcelist = resources
list_of_ids_to_delete = []
for resource in resourcelist:
list_of_ids_to_delete.append(resource.pk)
ids_query = Ids(ids=list_of_ids_to_delete)
q.add_query(ids_query)
q.delete(index=self.index_name)
def delete_index(self):
"""
Deletes this index from Elastic Search
Arguments:
None
Keyword Arguments:
None
Return: None
"""
self.se.delete_index(index=self.index_name)
def reindex(self, graphids=None, clear_index=True, batch_size=settings.BULK_IMPORT_BATCH_SIZE, quiet=False):
"""
Reindexes the index. By default this does nothing, it needs to be implemented in a subclass.
By default you can pass in a list of graph ids to trigger the reindex. This will loop through all resource instances of each graph type.
Example subclass command:
def reindex(self, clear_index=True):
PARCEL_GRAPHID = "e3c35dca-5e72-11ea-a2d3-dca90488358a"
super(CustomIndexName, self).reindex(graphids=[PARCEL_GRAPHID], clear_index=clear_index)
Keyword Arguments:
graphids -- list of graphs ids to trigger the reindex on, will get all resource instances of each graph id supplied
clear_index -- True(default) to clear all documents out of the index before reindexing begins
batch_size -- the number of records to index as a group, the larger the number to more memory required
Return: None
"""
if graphids is not None:
if clear_index:
self.delete_index()
self.prepare_index()
for graphid in graphids:
resources = Resource.objects.filter(graph_id=graphid)
self.index_resources(resources=resources, batch_size=batch_size, quiet=quiet)
else:
raise NotImplementedError
def index_resources_by_type(resource_types,
clear_index=True,
batch_size=settings.BULK_IMPORT_BATCH_SIZE):
"""
Indexes all resources of a given type(s)
Arguments:
resource_types -- array of graph ids that represent resource types
Keyword Arguments:
clear_index -- set to True to remove all the resources of the types passed in from the index before the reindexing operation
batch_size -- the number of records to index as a group, the larger the number to more memory required
"""
se = SearchEngineFactory().create()
datatype_factory = DataTypeFactory()
node_datatypes = {
str(nodeid): datatype
for nodeid, datatype in models.Node.objects.values_list(
'nodeid', 'datatype')
}
for resource_type in resource_types:
start = datetime.now()
resources = Resource.objects.filter(graph_id=str(resource_type))
graph_name = models.GraphModel.objects.get(
graphid=str(resource_type)).name
print "Indexing resource type '{0}'".format(graph_name)
result_summary = {'database': len(resources), 'indexed': 0}
if clear_index:
q = Query(se=se)
q.delete(index='resource', doc_type=str(resource_type))
with se.BulkIndexer(batch_size=batch_size,
refresh=True) as doc_indexer:
with se.BulkIndexer(batch_size=batch_size,
refresh=True) as term_indexer:
for resource in resources:
document, terms = resource.get_documents_to_index(
fetchTiles=True,
datatype_factory=datatype_factory,
node_datatypes=node_datatypes)
doc_indexer.add(index='resource',
doc_type=document['graph_id'],
id=document['resourceinstanceid'],
data=document)
for term in terms:
term_indexer.add(index='strings',
doc_type='term',
id=term['_id'],
data=term['_source'])
result_summary['indexed'] = se.es.count(
index='resource', doc_type=str(resource_type))['count']
status = 'Passed' if result_summary['database'] == result_summary[
'indexed'] else 'Failed'
print "Status: {0}, Resource Type: {1}, In Database: {2}, Indexed: {3}, Took: {4} seconds".format(
status, graph_name, result_summary['database'],
result_summary['indexed'], (datetime.now() - start).seconds)
class BaseIndex(object):
def __init__(self, index_name=None):
if index_name is None or index_name is "":
raise SearchIndexError("Index name is not defined")
self.se = SearchEngineFactory().create()
self.index_metadata = None
self.index_name = index_name
def prepare_index(self):
"""
Defines the Elastic Search mapping and settings for an index
Arguments:
None
Keyword Arguments:
None
Return: None
"""
if self.index_metadata is not None:
self.se.create_index(index=self.index_name,
body=self.index_metadata)
else:
raise SearchIndexError("No index metadata defined.")
def get_documents_to_index(self, resourceinstance, tiles):
"""
Gets a document to index into Elastic Search
Arguments:
resourceinstance -- resource instance object
tiles -- list of tiles that make up the resource instance
Keyword Arguments:
None
Return: tuple of (document, document id)
"""
raise NotImplementedError
def index_document(self, document=None, id=None):
"""
Indexes a document into Elastic Search
Arguments:
None
Keyword Arguments:
document -- the document to index
id -- the id of the document
Return: None
"""
if document is not None and id is not None:
self.se.index_data(index=self.index_name, body=document, id=id)
def bulk_index(self,
resources=None,
resource_type=None,
graph_name=None,
clear_index=True):
"""
Indexes a list of documents in bulk to Elastic Search
Arguments:
None
Keyword Arguments:
resources -- the list of resource instances to index
resource_type -- the type of resources being indexed
graph_name -- the name of the graph model that represents the resources being indexed
clear_index -- True(default) to remove all index records of type "resource_type" before indexing,
assumes that a field called "graph_id" exists on the indexed documents
Return: None
"""
start = datetime.now()
q = Query(se=self.se)
if clear_index:
term = Term(field="graph_id", term=str(resource_type))
q.add_query(term)
q.delete(index=self.index_name, refresh=True)
q = Query(se=self.se)
count_before = self.se.count(index=self.index_name, body=q.dsl)
result_summary = {"database": len(resources), "indexed": 0}
with self.se.BulkIndexer(batch_size=settings.BULK_IMPORT_BATCH_SIZE,
refresh=True) as indexer:
for resource in resources:
tiles = list(
models.TileModel.objects.filter(resourceinstance=resource))
document, doc_id = self.get_documents_to_index(resource, tiles)
if document is not None and id is not None:
indexer.add(index=self.index_name,
id=doc_id,
data=document)
result_summary["indexed"] = self.se.count(index=self.index_name,
body=q.dsl) - count_before
status = "Passed" if result_summary["database"] == result_summary[
"indexed"] else "Failed"
print("Custom Index - %s:" % self.index_name)
print(
" Status: {0}, Resource Type: {1}, In Database: {2}, Indexed: {3}, Took: {4} seconds"
.format(status, graph_name, result_summary["database"],
result_summary["indexed"],
(datetime.now() - start).seconds))
def delete_index(self):
"""
Deletes this index from Elastic Search
Arguments:
None
Keyword Arguments:
None
Return: None
"""
self.se.delete_index(index=self.index_name)
