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I am working currently on telecom analytics project and newbie in query optimisation. To show result in browser it takes a full minute while just 45,000 records are to be accessed. Could you please suggest on ways to reduce time for showing results.
I wrote following query to find call-duration of a person of age-group:
sigma=0
popn=len(Demo.objects.filter(age_group=age))
card_list=[Demo.objects.filter(age_group=age)[i].card_no
for i in range(popn)]
for card in card_list:
dic=Fact_table.objects.filter(card_no=card.aggregate(Sum('duration'))
sigma+=dic['duration__sum']
avgDur=sigma/popn
Above code is within for loop to iterate over age-groups.
Model is as follows:
class Demo(models.Model):
card_no=models.CharField(max_length=20,primary_key=True)
gender=models.IntegerField()
age=models.IntegerField()
age_group=models.IntegerField()
class Fact_table(models.Model):
pri_key=models.BigIntegerField(primary_key=True)
card_no=models.CharField(max_length=20)
duration=models.IntegerField()
time_8bit=models.CharField(max_length=8)
time_of_day=models.IntegerField()
isBusinessHr=models.IntegerField()
Day_of_week=models.IntegerField()
Day=models.IntegerField()
Thanks
Try that:
sigma=0
demo_by_age = Demo.objects.filter(age_group=age);
popn=demo_by_age.count() #One
card_list = demo_by_age.values_list('card_no', flat=True) # Two
dic = Fact_table.objects.filter(card_no__in=card_list).aggregate(Sum('duration') #Three
sigma = dic['duration__sum']
avgDur=sigma/popn
A statement like card_list=[Demo.objects.filter(age_group=age)[i].card_no for i in range(popn)] will generate popn seperate queries and database hits. The query in the for-loop will also hit the database popn times. As a general rule, you should try to minimize the amount of queries you use, and you should only select the records you need.
With a few adjustments to your code this can be done in just one query.
There's generally no need to manually specify a primary_key, and in all but some very specific cases it's even better not to define any. Django automatically adds an indexed, auto-incremental primary key field. If you need the card_no field as a unique field, and you need to find rows based on this field, use this:
class Demo(models.Model):
card_no = models.SlugField(max_length=20, unique=True)
...
SlugField automatically adds a database index to the column, essentially making selections by this field as fast as when it is a primary key. This still allows other ways to access the table, e.g. foreign keys (as I'll explain in my next point), to use the (slightly) faster integer field specified by Django, and will ease the use of the model in Django.
If you need to relate an object to an object in another table, use models.ForeignKey. Django gives you a whole set of new functionality that not only makes it easier to use the models, it also makes a lot of queries faster by using JOIN clauses in the SQL query. So for you example:
class Fact_table(models.Model):
card = models.ForeignKey(Demo, related_name='facts')
...
The related_name fields allows you to access all Fact_table objects related to a Demo instance by using instance.facts in Django. (See https://docs.djangoproject.com/en/dev/ref/models/fields/#module-django.db.models.fields.related)
With these two changes, your query (including the loop over the different age_groups) can be changed into a blazing-fast one-hit query giving you the average duration of calls made by each age_group:
age_groups = Demo.objects.values('age_group').annotate(duration_avg=Avg('facts__duration'))
for group in age_groups:
print "Age group: %s - Average duration: %s" % group['age_group'], group['duration_avg']
.values('age_group') selects just the age_group field from the Demo's database table. .annotate(duration_avg=Avg('facts__duration')) takes every unique result from values (thus each unique age_group), and for each unique result will fetch all Fact_table objects related to any Demo object within that age_group, and calculate the average of all the duration fields - all in a single query.
I want to get an entity key knowing entity ID and an ancestor.
ID is unique within entity group defined by the ancestor.
It seems to me that it's not possible using ndb interface. As I understand datastore it may be caused by the fact that this operation requires full index scan to perform.
The workaround I used is to create a computed property in the model, which will contain the id part of the key. I'm able now to do an ancestor query and get the key
class SomeModel(ndb.Model):
ID = ndb.ComputedProperty( lambda self: self.key.id() )
#classmethod
def id_to_key(cls, identifier, ancestor):
return cls.query(cls.ID == identifier,
ancestor = ancestor.key ).get( keys_only = True)
It seems to work, but are there any better solutions to this problem?
Update
It seems that for datastore the natural solution is to use full paths instead of identifiers. Initially I thought it'd be too burdensome. After reading dragonx answer I redesigned my application. To my suprise everything looks much simpler now. Additional benefits are that my entities will use less space and I won't need additional indexes.
I ran into this problem too. I think you do have the solution.
The better solution would be to stop using IDs to reference entities, and store either the actual key or a full path.
Internally, I use keys instead of IDs.
On my rest API, I used to do http://url/kind/id (where id looked like "123") to fetch an entity. I modified that to provide the complete ancestor path to the entity: http://url/kind/ancestor-ancestor-id (789-456-123), I'd then parse that string, generate a key, and then get by key.
Since you have full information about your ancestor and you know your id, you could directly create your key and get the entity, as follows:
my_key = ndb.Key(Ancestor, ancestor.key.id(), SomeModel, id)
entity = my_key.get()
This way you avoid making a query that costs more than a get operation both in terms of money and speed.
Hope this helps.
I want to make a little addition to dargonx's answer.
In my application on front-end I use string representation of keys:
str(instance.key())
When I need to make some changes with instence even if it is a descendant I use only string representation of its key. For example I have key_str -- argument from request to delete instance':
instance = Kind.get(key_str)
instance.delete()
My solution is using urlsafe to get item without worry about parent id:
pk = ndb.Key(Product, 1234)
usafe = LocationItem.get_by_id(5678, parent=pk).key.urlsafe()
# now can get by urlsafe
item = ndb.Key(urlsafe=usafe)
print item
For example, if I have: List A; and a String B;
What is the difference, in JDO (AppEngine), between the following two conditions in a query: B == A; and A.contains(B);?
Also, does the query in Slides 23-25 of http://dl.google.com/io/2009/pres/W_0415_Building_Scalable_Complex_App_Engines.pdf work efficiently in AppEngine (JDO) for more than 30 receivers? How so, especially since I read in AppEngine documentation that each contains() query can have a maximum of 30 items in the list. Do I not use a contains() query to imitate the above slides (written in Python)? If not, then how can I achieve the same results in JDO?
Any suggestions/comments are highly welcome. I'm trying to build a messaging system in AppEngine but having trouble trying to get used to the platform.
Thanks.
There's no difference - in App Engine, equality checks on lists are the same as checking for containment, due to the way things are indexed in the datastore.
By the query on slides 23-25, I presume you mean this one?
indexes = db.GqlQuery(
"SELECT __key__ FROM MessageIndex "
"WHERE receivers = :1", me)
keys = [k.parent() for k in indexes]
messages = db.get(keys)
This works just fine, as it's a list containment check as described above, and results in a single datastore query. The limitation you're thinking about is on the reverse: if you have a list, and you want to find a record that contains any item in that list, a subquery will be created for each element in the list.
Simple one really. In SQL, if I want to search a text field for a couple of characters, I can do:
SELECT blah FROM blah WHERE blah LIKE '%text%'
The documentation for App Engine makes no mention of how to achieve this, but surely it's a common enough problem?
BigTable, which is the database back end for App Engine, will scale to millions of records. Due to this, App Engine will not allow you to do any query that will result in a table scan, as performance would be dreadful for a well populated table.
In other words, every query must use an index. This is why you can only do =, > and < queries. (In fact you can also do != but the API does this using a a combination of > and < queries.) This is also why the development environment monitors all the queries you do and automatically adds any missing indexes to your index.yaml file.
There is no way to index for a LIKE query so it's simply not available.
Have a watch of this Google IO session for a much better and more detailed explanation of this.
i'm facing the same problem, but i found something on google app engine pages:
Tip: Query filters do not have an explicit way to match just part of a string value, but you can fake a prefix match using inequality filters:
db.GqlQuery("SELECT * FROM MyModel WHERE prop >= :1 AND prop < :2",
"abc",
u"abc" + u"\ufffd")
This matches every MyModel entity with a string property prop that begins with the characters abc. The unicode string u"\ufffd" represents the largest possible Unicode character. When the property values are sorted in an index, the values that fall in this range are all of the values that begin with the given prefix.
http://code.google.com/appengine/docs/python/datastore/queriesandindexes.html
maybe this could do the trick ;)
Altough App Engine does not support LIKE queries, have a look at the properties ListProperty and StringListProperty. When an equality test is done on these properties, the test will actually be applied on all list members, e.g., list_property = value tests if the value appears anywhere in the list.
Sometimes this feature might be used as a workaround to the lack of LIKE queries. For instance, it makes it possible to do simple text search, as described on this post.
You need to use search service to perform full text search queries similar to SQL LIKE.
Gaelyk provides domain specific language to perform more user friendly search queries. For example following snippet will find first ten books sorted from the latest ones with title containing fern
and the genre exactly matching thriller:
def documents = search.search {
select all from books
sort desc by published, SearchApiLimits.MINIMUM_DATE_VALUE
where title =~ 'fern'
and genre = 'thriller'
limit 10
}
Like is written as Groovy's match operator =~.
It supports functions such as distance(geopoint(lat, lon), location) as well.
App engine launched a general-purpose full text search service in version 1.7.0 that supports the datastore.
Details in the announcement.
More information on how to use this: https://cloud.google.com/appengine/training/fts_intro/lesson2
Have a look at Objectify here , it is like a Datastore access API. There is a FAQ with this question specifically, here is the answer
How do I do a like query (LIKE "foo%")
You can do something like a startWith, or endWith if you reverse the order when stored and searched. You do a range query with the starting value you want, and a value just above the one you want.
String start = "foo";
... = ofy.query(MyEntity.class).filter("field >=", start).filter("field <", start + "\uFFFD");
Just follow here:
init.py#354">http://code.google.com/p/googleappengine/source/browse/trunk/python/google/appengine/ext/search/init.py#354
It works!
class Article(search.SearchableModel):
text = db.TextProperty()
...
article = Article(text=...)
article.save()
To search the full text index, use the SearchableModel.all() method to get an
instance of SearchableModel.Query, which subclasses db.Query. Use its search()
method to provide a search query, in addition to any other filters or sort
orders, e.g.:
query = article.all().search('a search query').filter(...).order(...)
I tested this with GAE Datastore low-level Java API. Me and works perfectly
Query q = new Query(Directorio.class.getSimpleName());
Filter filterNombreGreater = new FilterPredicate("nombre", FilterOperator.GREATER_THAN_OR_EQUAL, query);
Filter filterNombreLess = new FilterPredicate("nombre", FilterOperator.LESS_THAN, query+"\uFFFD");
Filter filterNombre = CompositeFilterOperator.and(filterNombreGreater, filterNombreLess);
q.setFilter(filter);
In general, even though this is an old post, a way to produce a 'LIKE' or 'ILIKE' is to gather all results from a '>=' query, then loop results in python (or Java) for elements containing what you're looking for.
Let's say you want to filter users given a q='luigi'
users = []
qry = self.user_model.query(ndb.OR(self.user_model.name >= q.lower(),self.user_model.email >= q.lower(),self.user_model.username >= q.lower()))
for _qry in qry:
if q.lower() in _qry.name.lower() or q.lower() in _qry.email.lower() or q.lower() in _qry.username.lower():
users.append(_qry)
It is not possible to do a LIKE search on datastore app engine, how ever creating an Arraylist would do the trick if you need to search a word in a string.
#Index
public ArrayList<String> searchName;
and then to search in the index using objectify.
List<Profiles> list1 = ofy().load().type(Profiles.class).filter("searchName =",search).list();
and this will give you a list with all the items that contain the world you did on the search
If the LIKE '%text%' always compares to a word or a few (think permutations) and your data changes slowly (slowly means that it's not prohibitively expensive - both price-wise and performance-wise - to create and updates indexes) then Relation Index Entity (RIE) may be the answer.
Yes, you will have to build additional datastore entity and populate it appropriately. Yes, there are some constraints that you will have to play around (one is 5000 limit on the length of list property in GAE datastore). But the resulting searches are lightning fast.
For details see my RIE with Java and Ojbectify and RIE with Python posts.
"Like" is often uses as a poor-man's substitute for text search. For text search, it is possible to use Whoosh-AppEngine.
Simple one really. In SQL, if I want to search a text field for a couple of characters, I can do:
SELECT blah FROM blah WHERE blah LIKE '%text%'
The documentation for App Engine makes no mention of how to achieve this, but surely it's a common enough problem?
BigTable, which is the database back end for App Engine, will scale to millions of records. Due to this, App Engine will not allow you to do any query that will result in a table scan, as performance would be dreadful for a well populated table.
In other words, every query must use an index. This is why you can only do =, > and < queries. (In fact you can also do != but the API does this using a a combination of > and < queries.) This is also why the development environment monitors all the queries you do and automatically adds any missing indexes to your index.yaml file.
There is no way to index for a LIKE query so it's simply not available.
Have a watch of this Google IO session for a much better and more detailed explanation of this.
i'm facing the same problem, but i found something on google app engine pages:
Tip: Query filters do not have an explicit way to match just part of a string value, but you can fake a prefix match using inequality filters:
db.GqlQuery("SELECT * FROM MyModel WHERE prop >= :1 AND prop < :2",
"abc",
u"abc" + u"\ufffd")
This matches every MyModel entity with a string property prop that begins with the characters abc. The unicode string u"\ufffd" represents the largest possible Unicode character. When the property values are sorted in an index, the values that fall in this range are all of the values that begin with the given prefix.
http://code.google.com/appengine/docs/python/datastore/queriesandindexes.html
maybe this could do the trick ;)
Altough App Engine does not support LIKE queries, have a look at the properties ListProperty and StringListProperty. When an equality test is done on these properties, the test will actually be applied on all list members, e.g., list_property = value tests if the value appears anywhere in the list.
Sometimes this feature might be used as a workaround to the lack of LIKE queries. For instance, it makes it possible to do simple text search, as described on this post.
You need to use search service to perform full text search queries similar to SQL LIKE.
Gaelyk provides domain specific language to perform more user friendly search queries. For example following snippet will find first ten books sorted from the latest ones with title containing fern
and the genre exactly matching thriller:
def documents = search.search {
select all from books
sort desc by published, SearchApiLimits.MINIMUM_DATE_VALUE
where title =~ 'fern'
and genre = 'thriller'
limit 10
}
Like is written as Groovy's match operator =~.
It supports functions such as distance(geopoint(lat, lon), location) as well.
App engine launched a general-purpose full text search service in version 1.7.0 that supports the datastore.
Details in the announcement.
More information on how to use this: https://cloud.google.com/appengine/training/fts_intro/lesson2
Have a look at Objectify here , it is like a Datastore access API. There is a FAQ with this question specifically, here is the answer
How do I do a like query (LIKE "foo%")
You can do something like a startWith, or endWith if you reverse the order when stored and searched. You do a range query with the starting value you want, and a value just above the one you want.
String start = "foo";
... = ofy.query(MyEntity.class).filter("field >=", start).filter("field <", start + "\uFFFD");
Just follow here:
init.py#354">http://code.google.com/p/googleappengine/source/browse/trunk/python/google/appengine/ext/search/init.py#354
It works!
class Article(search.SearchableModel):
text = db.TextProperty()
...
article = Article(text=...)
article.save()
To search the full text index, use the SearchableModel.all() method to get an
instance of SearchableModel.Query, which subclasses db.Query. Use its search()
method to provide a search query, in addition to any other filters or sort
orders, e.g.:
query = article.all().search('a search query').filter(...).order(...)
I tested this with GAE Datastore low-level Java API. Me and works perfectly
Query q = new Query(Directorio.class.getSimpleName());
Filter filterNombreGreater = new FilterPredicate("nombre", FilterOperator.GREATER_THAN_OR_EQUAL, query);
Filter filterNombreLess = new FilterPredicate("nombre", FilterOperator.LESS_THAN, query+"\uFFFD");
Filter filterNombre = CompositeFilterOperator.and(filterNombreGreater, filterNombreLess);
q.setFilter(filter);
In general, even though this is an old post, a way to produce a 'LIKE' or 'ILIKE' is to gather all results from a '>=' query, then loop results in python (or Java) for elements containing what you're looking for.
Let's say you want to filter users given a q='luigi'
users = []
qry = self.user_model.query(ndb.OR(self.user_model.name >= q.lower(),self.user_model.email >= q.lower(),self.user_model.username >= q.lower()))
for _qry in qry:
if q.lower() in _qry.name.lower() or q.lower() in _qry.email.lower() or q.lower() in _qry.username.lower():
users.append(_qry)
It is not possible to do a LIKE search on datastore app engine, how ever creating an Arraylist would do the trick if you need to search a word in a string.
#Index
public ArrayList<String> searchName;
and then to search in the index using objectify.
List<Profiles> list1 = ofy().load().type(Profiles.class).filter("searchName =",search).list();
and this will give you a list with all the items that contain the world you did on the search
If the LIKE '%text%' always compares to a word or a few (think permutations) and your data changes slowly (slowly means that it's not prohibitively expensive - both price-wise and performance-wise - to create and updates indexes) then Relation Index Entity (RIE) may be the answer.
Yes, you will have to build additional datastore entity and populate it appropriately. Yes, there are some constraints that you will have to play around (one is 5000 limit on the length of list property in GAE datastore). But the resulting searches are lightning fast.
For details see my RIE with Java and Ojbectify and RIE with Python posts.
"Like" is often uses as a poor-man's substitute for text search. For text search, it is possible to use Whoosh-AppEngine.