I currently have an application running on appengine and I am executing a few jobs using the deferred library, some of these tasks run daily, while some of them are executed once a month. Most of these tasks query Datastore to retrieve documents and then store the entities in an index (Search API). Some of these tables are replaced monthly and I have to run these tasks on all entities (4~5M).
One exemple of such a task is:
def addCompaniesToIndex(cursor=None, n_entities=0, mindate=None):
#get index
BATCH_SIZE = 200
cps, next_cursor, more = Company.query().
fetch_page(BATCH_SIZE,
start_cursor=cursor)
doc_list = []
for i in range(0, len(cps)):
cp = cps[i]
#create a Index Document using the Datastore entity
#this document has only about 5 text fields and one date field
cp_doc = getCompanyDocument(cp)
doc_list.append(cp_doc)
index = search.Index(name='Company')
index.put(doc_list)
n_entities += len(doc_list)
if more:
logging.debug('Company: %d added to index', n_entities)
#to_put[:] = []
doc_list[:] = []
deferred.defer(addCompaniesToIndex,
cursor=next_cursor,
n_entities=n_entities,
mindate=mindate)
else:
logging.debug('Finished Company index creation (%d processed)', n_entities)
When I run one task only, the execution takes around 4-5s per deferred task, so indexing my 5M entities would take about 35 hours.
Another thing is that when I run an update on another index (eg, one of the daily updates) using a different deferred task on the same queue, both are executed a lot slower. And start taking about 10-15 seconds per deferred call which is just unbearable.
My question is: is there a way to do this faster and scale the push queue to more than one job running each time? Or should I use a different approach for this problem?
Thanks in advance,
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