Need to optimize Neo4j Query - performance

I am creating a social media app whose back-end is Neo4j. Here, I want to fetch friends activities on user's homepage. I have put a limit of 10 activities per scroll.
This is my current Neo4j Query:
MATCH (m:Person { id: '$id'})-[:FOLLOWS*1..1]->(f:Person)-[:HAS_ACTIVITY]->(la:Activity)-[:NEXT*0..]->(act:Activity)
WHERE act.verb IN ['post' ,'post_media_item' ,'watch_activity']
RETURN f, act ORDER BY act.published DESC LIMIT 10
In the above query user are depicted by Person node and User-feed is depicted by Activity node. "m" is current user whose friends "f" are depicted by the relationship "Follows". Activity for each user are interlinked with the relationship "NEXT" and are linked with Person node with relationship "HAS_ACTIVITY". It is intentional to keep maximum hops blank as a Person can have any number of activities.
For this query as Friend List of a person grows, so does the overall query execution time.
Currently for a user having 50 friends the time taken is 3-5 seconds.
I have to perform further aggregation from the result of this query which takes query execution time to 7-10 seconds.
Please find attached a screenshot of PROFILE and EXPLAIN:
How can I optimize my Cypher query so that I get the quickest result irrespective of a number of friends?
Neo4j Version used: 3.0.6

A simple thing would be to update to Neo4j 3.5.x at least.
If a person has all activities linked to it with HAS_ACTIVITY relationship, why do you need to further traverse the NEXT relationship? Would the following query not suffice?
MATCH (m:Person { id: '58c1370350b91a0005be0136'})-[:FOLLOWS*1..1]->(f:Person)-[:HAS_ACTIVITY]->(la:Activity)
WHERE la.verb IN ['post' ,'post_media_item' ,'watch_activity']
RETURN f, la ORDER BY la.published DESC LIMIT 10

Related

Query that discards duplicate keys with parse.com SDK?

I'm researching how to implement leaderboards for my game with the parse.com SDK, my plan is to submit a score for the user every time they finish a level, attached to a "parent" leaderboard. I need to submit all scores because I need to retrieve leaderboards within time ranges (eg "all time", "last week", "last month", etc). The problem is, there'll be multiple scores for each user on the same leaderboard, and I only need to highest one. Is there a way to drop duplicate keys from a query? Is this the correct strategy? Everything else (sorting, paging, etc) seems to be in place.
Thanks.
You just need a table with 'User_id', 'Score', 'Level', and 'Date' (or whatever you need). Each time that a player finishes a level, you put the score into the table.
Then you have to calculate each (all time, last week, etc) in the query.
E.g.
10 Highs of the day:
SELECT TOP 10 User_id, Score, Date FROM Scores
WHERE Date = getdate()
ORDER BY Score DESC
I don't know if I understood the question. Let me know if I didn't.
Hope it helps.
As far as I understand from your question you want to retrieve data from Parse class. At the same time you want to eliminate the duplicate entry because user has multiple scores in different days. So to get the highest one, you have to query the class via query (based on SDK Android,iOS) and order by descending(based on your criteria), then obtain the first item in the result.
Or you can get the user all scores and create a structure where you can store the user scores as array list day by day. Based on day you can get the latest max or min scores. I hope I understand your question.
Hope this helps.Regards

Efficient way to query

My app has a class that saves picture that users upload. Each object in the class has a city property that holds the name of the city that the picture was taken at, and a like property that tracks the number of likes.
I want to be able to send a query that returns one picture per city and each picture should have the highest ranking of likes in the city it belongs to. How can I do that?
One way which I first thought about is doing multiple queries by fetching the most liked picture of a city and save it in an array, and then do the same to other cities.
However, each country has more than one city, thus it's not that efficient.
Parse doesn't support the ordinary operations used in databases. Besides, I tried to use a compound query. Unfortunately, I can't set limit or ordering on the subqueries. Any good solution for this?
It would be easy using group by. Unfortunately, Parse does not support "select distinct" or "group by" features.
As you've suggested you need to fetch for each country all the cities, and for each one get the top most rated photo.
BUT, since Parse has strict restrictions on the duration time execution of a request ( 3 sec for an event listener, 7 sec for a custom function ), I suggest you to do this in a background job, saving in a new table the top rated photo for each city. In this way you can easily query the db from client. The Background jobs can be executed up to 15 minuted before parse drop them, so you could make that kind of queries without timeouts.
Hope it helps

Is it a good idea to store and access an active query resultset in Coldfusion vs re-quering the database?

I have a product search engine using Coldfusion8 and MySQL 5.0.88
The product search has two display modes: Multiple View and Single View.
Multiple displays basic record info, Single requires additional data to be polled from the database.
Right now a user does a search and I'm polling the database for
(a) total records and
(b) records FROM to TO.
The user always goes to Single view from his current resultset, so my idea was to store the current resultset for each user and not have to query the database again to get (waste a) overall number of records and (waste b) a the single record I already queried before AND then getting the detail information I still need for the Single view.
However, I'm getting nowhere with this.
I cannot cache the current resultset-query, because it's unique to each user(session).
The queries are running inside a CFINVOKED method inside a CFC I'm calling through AJAX, so the whole query runs and afterwards the CFC and CFINVOKE method are discarded, so I can't use query of query or variables.cfc_storage.
So my idea was to store the current resultset in the Session scope, which will be updated with every new search, the user runs (either pagination or completely new search). The maximum results stored will be the number of results displayed.
I can store the query allright, using:
<cfset Session.resultset = query_name>
This stores the whole query with results, like so:
query
CACHED: false
EXECUTIONTIME: 2031
SQL: SELECT a.*, p.ek, p.vk, p.x, p.y
FROM arts a
LEFT JOIN p ON
...
LEFT JOIN f ON
...
WHERE a.aktiv = "ja"
AND
... 20 conditions ...
SQLPARAMETERS: [array]
1) ... 20+ parameters
RESULTSET:
[Record # 1]
a: true
style: 402
price: 2.3
currency: CHF
...
[Record # 2]
a: true
style: 402abc
...
This would be overwritten every time a user does a new search. However, if a user wants to see the details of one of these items, I don't need to query (total number of records & get one record) if I can access the record I need from my temp storage. This way I would save two database trips worth 2031 execution time each to get data which I already pulled before.
The tradeoff would be every user having a resultset of up to 48 results (max number of items per page) in Session.scope.
My questions:
1. Is this feasable or should I requery the database?
2. If I have a struture/array/object like a the above, how do I pick the record I need out of it by style number = how do I access the resultset? I can't just loop over the stored query (tried this for a while now...).
Thanks for help!
KISS rule. Just re-query the database unless you find the performance is really an issue. With the correct index, it should scales pretty well. When the it is an issue, you can simply add query cache there.
QoQ would introduce overhead (on the CF side, memory & computation), and might return stale data (where the query in session is older than the one on DB). I only use QoQ when the same query is used on the same view, but not throughout a Session time span.
Feasible? Yes, depending on how many users and how much data this stores in memory, it's probably much better than going to the DB again.
It seems like the best way to get the single record you want is a query of query. In CF you can create another query that uses an existing query as it's data source. It would look like this:
<cfquery name="subQuery" dbtype="query">
SELECT *
FROM Session.resultset
WHERE style = #SelectedStyleVariable#
</cfquery>
note that if you are using CFBuilder, it will probably scream Error at you for not having a datasource, this is a bug in CFBuilder, you are not required to have a datasource if your DBType is "query"
Depending on how many records, what I would do is have the detail data stored in application scope as a structure where the ID is the key. Something like:
APPLICATION.products[product_id].product_name
.product_price
.product_attribute
Then you would really only need to query for the ID of the item on demand.
And to improve the "on demand" query, you have at least two "in code" options:
1. A query of query, where you query the entire collection of items once, and then query from that for the data you need.
2. Verity or SOLR to index everything and then you'd only have to query for everything when refreshing your search collection. That would be tons faster than doing all the joins for every single query.

Random exhaustive (non-repeating) selection from a large pool of entries

Suppose I have a large (300-500k) collection of text documents stored in the relational database. Each document can belong to one or more (up to six) categories. I need users to be able to randomly select documents in a specific category so that a single entity is never repeated, much like how StumbleUpon works.
I don't really see a way I could implement this using slow NOT IN queries with large amount of users and documents, so I figured I might need to implement some custom data structure for this purpose. Perhaps there is already a paper describing some algorithm that might be adapted to my needs?
Currently I'm considering the following approach:
Read all the entries from the database
Create a linked list based index for each category from the IDs of documents belonging to the this category. Shuffle it
Create a Bloom Filter containing all of the entries viewed by a particular user
Traverse the index using the iterator, randomly select items using Bloom Filter to pick not viewed items.
If you track via a table what entries that the user has seen... try this. And I'm going to use mysql because that's the quickest example I can think of but the gist should be clear.
On a link being 'used'...
insert into viewed (userid, url_id) values ("jj", 123)
On looking for a link...
select p.url_id
from pages p left join viewed v on v.url_id = p.url_id
where v.url_id is null
order by rand()
limit 1
This causes the database to go ahead and do a 1 for 1 join, and your limiting your query to return only one entry that the user has not seen yet.
Just a suggestion.
Edit: It is possible to make this one operation but there's no guarantee that the url will be passed successfully to the user.
It depend on how users get it's random entries.
Option 1:
A user is paging some entities and stop after couple of them. for example the user see the current random entity and then moving to the next one, read it and continue it couple of times and that's it.
in the next time this user (or another) get an entity from this category the entities that already viewed is clear and you can return an already viewed entity.
in that option I would recommend save a (hash) set of already viewed entities id and every time user ask for a random entity- randomally choose it from the DB and check if not already in the set.
because the set is so small and your data is so big, the chance that you get an already viewed id is so small, that it will take O(1) most of the time.
Option 2:
A user is paging in the entities and the viewed entities are saving between all users and every time user visit your page.
in that case you probably use all the entities in each category and saving all the viewed entites + check whether a entity is viewed will take some time.
In that option I would get all the ids for this topic- shuffle them and store it in a linked list. when you want to get a random not viewed entity- just get the head of the list and delete it (O(1)).
I assume that for any given <user, category> pair, the number of documents viewed is pretty small relative to the total number of documents available in that category.
So can you just store indexed triples <user, category, document> indicating which documents have been viewed, and then just take an optimistic approach with respect to randomly selected documents? In the vast majority of cases, the randomly selected document will be unread by the user. And you can check quickly because the triples are indexed.
I would opt for a pseudorandom approach:
1.) Determine number of elements in category to be viewed (SELECT COUNT(*) WHERE ...)
2.) Pick a random number in range 1 ... count.
3.) Select a single document (SELECT * FROM ... WHERE [same as when counting] ORDER BY [generate stable order]. Depending on the SQL dialect in use, there are different clauses that can be used to retrieve only the part of the result set you want (MySQL LIMIT clause, SQLServer TOP clause etc.)
If the number of documents is large the chance serving the same user the same document twice is neglibly small. Using the scheme described above you don't have to store any state information at all.
You may want to consider a nosql solution like Apache Cassandra. These seem to be ideally suited to your needs. There are many ways to design the algorithm you need in an environment where you can easily add new columns to a table (column family) on the fly, with excellent support for a very sparsely populated table.
edit: one of many possible solutions below:
create a CF(column family ie table) for each category (creating these on-the-fly is quite easy).
Add a row to each category CF for each document belonging to the category.
Whenever a user hits a document, you add a column with named and set it to true to the row. Obviously this table will be huge with millions of columns and probably quite sparsely populated, but no problem, reading this is still constant time.
Now finding a new document for a user in a category is simply a matter of selecting any result from select * where == null.
You should get constant time writes and reads, amazing scalability, etc if you can accept Cassandra's "eventually consistent" model (ie, it is not mission critical that a user never get a duplicate document)
I've solved similar in the past by indexing the relational database into a document oriented form using Apache Lucene. This was before the recent rise of NoSQL servers and is basically the same thing, but it's still a valid alternative approach.
You would create a Lucene Document for each of your texts with a textId (relational database id) field and multi valued categoryId and userId fields. Populate the categoryId field appropriately. When a user reads a text, add their id to the userId field. A simple query will return the set of documents with a given categoryId and without a given userId - pick one randomly and display it.
Store a users past X selections in a cookie or something.
Return the last selections to the server with the users new criteria
Randomly choose one of the texts satisfying the criteria until it is not a member of the last X selections of the user.
Return this choice of text and update the list of last X selections.
I would experiment to find the best value of X but I have in mind something like an X of say 16?

Mongo multiple queries or database normalization

I'm using MongoDB for my database. The query that I'm currently working on revealed a possible deficiency in my schema. Below is the relevant layout of my collections. Note that games.players is an array of 2 players since the game is chess.
users {_id, username, ...}
games {_id, players[], ...}
msgs {_id, username, gameid, time, msg}
The data that I need is:
All msgs for games which a user is in which is newer than a given timestamp.
In a SQL database, my query would look similar to:
SELECT * FROM msgs WHERE time>=$time AND gameid IN
(SELECT _id FROM games WHERE players=$username);
But, Mongo isn't a relational database, so doesn't support sub-queries or joins. I see two possible solutions. What would be better performance-wise and efficiency-wise?
Multiple Queries
Select games the user is in, then use $in to match msgs.gameid by.
Other?
Normalization
Make users.games contain all games a user is in.
Copy games.players to msgs.players by msgs.gameid
etc.,
I'm a relative newbie to MongoDB, but I find my self frequently using a combination of the two approaches. Some things - e.g. user names - are frequently duplicated to simplify queries used for display, but any time I need to do more than display information, I wind up writing multiple queries, sometimes 2 or 3 levels deep, using $in, to gather all the documents I need to work with for a given operation.
You can "normalize" yourself. I would add an array to users that list the games he is a member of;
users {_id, username, games={game1,game2,game3}}
now you can do a query on msgs where the time>time$ and the {games._id "is in" users.games}
You will have to maintain the games list on each user.

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