Salesforce SOQL query length and efficiency - performance

I am trying to solve a problem of deleting only rows matching two criteria, each being a list of ids. Now these Ids are in pairs, if the item to be deleted has one, it must have the second one in the pair, so just using two in clauses will not work. I have come up with two solutions.
1) Use the two in clauses but then loop over the items and check that the two ids in question appear in the correct pairing.
I.E.
for(Object__c obj : [SELECT Id FROM Object__c WHERE Relation1__c in :idlist1 AND Relation2__c in:idlist2]){
if(preConstructedPairingsAsString.contains(''+obj.Relation1__c+obj.Relation2__c)){
listToDelete.add(obj);
}
}
2) Loop over the ids and build an admittedly long query.
I like the second choice because I only get the items I need and can just throw the list into delete but I know that salesforce has hangups with SOQL queries. Is there a penalty to the second option? Is it better to build and query off a long string or to get more objects than necessary and filter?

In general you want to put as much logic as you can into soql queries because that won't use any script statements and they execute faster than your code. However, there is a 10k character limit on soql queries (can be raised to 20k) so based on my back of the envelope calculations you'd only be able to put in 250 id pairs or so before hitting that limit.
I would go with option 1 or if you really care about efficiency you can create a formula field on the object that pairs the ids and filter on that.
formula: relation1__c + '-' + relation2__c
for(list<Object__c> objs : [SELECT Id FROM Object__c WHERE formula__c in :idpairs]){
delete objs;
}

Related

Neo4j building initial graph is slow

I am trying to build out a social graph between 100k users. Users can sync other social media platforms or upload their own contacts. Building each relationship takes about 200ms. Currently, I have everything uploaded on a queue so it can run in the background, but ideally, I can complete it within the HTTP request window. I've tried a few things and received a few warnings.
Added an index to the field pn
Getting a warning This query builds a cartesian product between disconnected patterns. - I understand why I am getting this warning, but no relationship exists and that's what I am building in this initial call.
MATCH (p1:Person {userId: "....."}), (p2:Person) WHERE p2.pn = "....." MERGE (p1)-[:REL]->(p2) RETURN p1, p2
Any advice on how to make it faster? Ideally, each relationship creation is around 1-2ms.
You may want to EXPLAIN the query and make sure that NodeIndexSeeks are being used, and not NodeByLabelScan. You also mentioned an index on :Person(pn), but you have a lookup on :Person(userId), so you might be missing an index there, unless that was a typo.
Regarding the cartesian product warning, disregard it, the cartesian product is necessary in order to get the nodes to create the relationship, this should be a 1 x 1 = 1 row operation so it's only going to be costly if multiple nodes are being matched per side, or if index lookups aren't being used.
If these are part of some batch load operation, then you may want to make your query apply in batches. So if 100 contacts are being loaded by a user, you do NOT want to execute 100 queries each, with each query adding a single contact. Instead, pass as a parameter the list of contacts, then UNWIND the list and apply the query once to process the entire batch.
Something like:
UNWIND $batch as row
MATCH (p1:Person {pn: row.p1}), (p2:Person {pn: row.p2)
MERGE (p1)-[:REL]->(p2)
RETURN p1, p2
It's usually okay to batch 10k or so entries at a time, though you can adjust that depending on the complexity of the query
Check out this blog entry for how to apply this approach.
https://dzone.com/articles/tips-for-fast-batch-updates-of-graph-structures-wi
You can use the index you created on Person by suggesting a planner hint.
Reference: https://neo4j.com/docs/cypher-manual/current/query-tuning/using/#query-using-index-hint
CREATE INDEX ON :Person(pn);
MATCH (p1:Person {userId: "....."})
WITH p1
MATCH (p2:Person) using index p2:Person(pn)
WHERE p2.pn = "....."
MERGE (p1)-[:REL]->(p2)
RETURN p1, p2

Why is a paginated query slower than a plain one with Spring Data?

Given I have a simple query:
List<Customer> findByEntity(String entity);
This query returns 7k records in 700ms.
Page<Customer> findByEntity(String entity, Pageable pageable);
this query returns 10 records in 1080ms. I am aware of the additional count query for pagination, but still something seems off. Also one strange thing I've noticed is that if I increase page size from 10 to 1900, response time is exactly the same around 1080 ms.
Any suggestions?
It might indeed be the count query that's expensive here. If you insist on knowing about the total number of elements matching in the collection there's unfortunately no way around that additional query. However there are two possibilities to avoid more of the overhead if you're able to sacrifice on information returned:
Using Slice as return type — Slice doesn't expose a method to find out about the total number of elements but it allows you to find out about whether a next slice is available. We avoid the count query here by reading one more element than requested and using its (non-)presence as indicator of the availability of a next slice.
Using List as return type — That will simply apply the pagination parameters to the query and return the window of elements selected. However it leaves you with no information about whether subsequent data is available.
Method with pagination runs two query:
1) select count(e.id) from Entity e //to get number of total records
2) select e from Entity e limit 10 [offset 10] //'offset 10' is used for next pages
The first query runs slow on 7k records, IMHO.
Upcoming release Ingalis of Spring Data will use improved algorithm for paginated queries (more info).
Any suggestions?
I think using a paginated query with 7k records it's useless. You should limit it.

Use ParseQuery to get the first item found from list

I want to query Parse in order to retrieve the first object found in a given list, in the given list's order.
My code looks pretty much like this:
query = getQuery(MyClass.class).whereContainedIn("FieldName", itemList);
networkQuery.getFirstInBackground(...);
What I need, specifically, is to retrieve the first item found in the list, meaning that if I provide it a list of numbers in ascending order, I wish to retrieve the object corresponding with the smallest number possible.
I'm not sure this is how getFirstInBackground() works, I know it fetches a single result, but how can I assure the search is made according to the order of the list I provided as argument?
You have to order your query using the -orderByAscending (or Descending, i can't remember) method. It takes the column name parameter.
So something simple and easy to understand (but I'm sure you've understood already) is to order by ascending "Age" (example), and your first result in the array will be the smallest Age.
Once your query is ordered, just set a -limit to it. It's the number of results the query will return, if you only want the five firsts, set a limit of 5. or 20. The maximum is 1000.
If you also would like to skip the 3 first results because you know they're not interesting (and I'm just elaborating out of your question's scope here), you can use the -skip method, to skip the first X results.
This should do the trick to build your query. Set all those parameters and then execute your query and you'll have correct results.
EDIT : After re-reading your question I'm not sure I'm answering what you're asking. Please elaborate if I'm not.
Find the minimum value in itemList yourself, and qualify the query with that using equalTo.
// is this javascript? if so, underscorejs is very useful
var _ = require('underscore');
var minItem = _.min(itemList); // you can add an optional iteratee function that can minimize any computation over the list
query.equalTo("FieldName", minItem);
query.getFirstInBackground(...);
Edit
Parse.Query ordering applies only to sortable types, like strings and numbers. The ordering hoped for in the question is on the min() value of an array attribute. If such a thing were available, then a getFirst query would work.
What you need can still be done with find(). Since a small number of rows will have FieldName values contained in itemList, you can just do a find() and pick out the minimum from those few results...
query.find().then(function(results) {
return _.min(results, function(result) {
return result.get("FieldName");
});
});

Windows Azure Paging Large Datasets Solution

I'm using Windows Azure Table Storage to store millions of entities, however I'm trying to figure out the best solution that easily allows for two things:
1) a search on an entity, will retrieve that entity and at least (pageSize) number of entities either side of that entity
2) if there are more entities beyond (pageSize) number of entities either side of that entity, then page next or page previous links are shown, this will continue until either the start or end is reached.
3) the order is reverse chronological order
I've decided that the PartitionKey will be the Title provided by the user as each container is unique in the system. The RowKey is Steve Marx's lexiographical algorithm:
http://blog.smarx.com/posts/using-numbers-as-keys-in-windows-azure
which when converted to javascript instead of c# looks like this:
pad(new Date(100000000 * 86400000).getTime() - new Date().getTime(), 19) + "_" + uuid()
uuid() is a javascript function that returns a guid and pad adds zeros up to 19 chars in length. So records in the system look something like this:
PK RK
TEST 0008638662595845431_ecf134e4-b10d-47e8-91f2-4de9c4d64388
TEST 0008638662595845432_ae7bb505-8594-43bc-80b7-6bd34bb9541b
TEST 0008638662595845433_d527d215-03a5-4e46-8a54-10027b8e23f8
TEST 0008638662595845434_a2ebc3f4-67fe-43e2-becd-eaa41a4132e2
This pattern allows for every new entity inserted to be at the top of the list which satisfies point number 3 above.
With a nice way of adding new records in the system I thought then I would create a mechanism that looks at the first half of the RowKey i.e. 0008638662595845431_ part and does a greater than or less than comparison depending on which direction of the already found item. In other words to get the row immediately before 0008638662595845431 I would do a query like so:
var tableService = azure.createTableService();
var minPossibleDateTimeNumber = pad(new Date(-100000000*86400000).getTime() - new Date().getTime(), 19);
tableService.getTable('testTable', function (error) {
if (error === null) {
var query = azure.TableQuery
.select()
.from('testTable')
.where('PartitionKey eq ?', 'TEST')
.and('RowKey gt ?', minPossibleDateTimeNumber + '_')
.and('RowKey lt ?', '0008638662595845431_')
.and('Deleted eq ?', 'false');
If the results returned are greater than 1000 and azure gives me a continuation token, then I thought I would remember the last items RowKey i.e. the number part 0008638662595845431. So now the next query will have the remembered value as the starting value etc.
I am using Windows Azure Node.Js SDK and language is javascript.
Can anybody see gotcha's or problems with this approach?
I do not see how this can work effectively and efficiently, especially to get the rows for a previous page.
To be efficient, the prefix of your “key” needs to be a serially incrementing or decrementing value, instead of being based on a timestamp. A timestamp generated value would have duplicates as well as holes, making mapping page size to row count at best inefficient and at worst difficult to determine.
Also, this potential algorithm is dependent on a single partition key, destroying table scalability.
The challenge here would be to have a method of generating a serially incremented key. One solution is to use a SQL database and performing an atomic update on a single row, such that an incrementing or decrementing value is produced in sequence. Something like UPDATE … SET X = X + 1 and return X. Maybe using a stored procedure.
So the key could be a zero left padded serially generated number. Split such that say the first N digits of the number is the partition key and remaining M digits are the row key.
For example
PKey RKey
00001 10321
00001 10322
….
00954 98912
Now, since the rows are in sequence it is possible to write a query with the exact key range for the page size.
Caveat. There is a small risk of a failure occurring between generating a serial key and writing to table storage. In which case, there may be holes in the table. However, your paging algorithm should be able to detect and work around such instances quite easily by specify a page size slightly larger than necessary or by retrying with an adjusted range.

Improve SQL Server 2005 Query Performance

I have a course search engine and when I try to do a search, it takes too long to show search results. You can try to do a search here
http://76.12.87.164/cpd/testperformance.cfm
At that page you can also see the database tables and indexes, if any.
I'm not using Stored Procedures - the queries are inline using Coldfusion.
I think I need to create some indexes but I'm not sure what kind (clustered, non-clustered) and on what columns.
Thanks
You need to create indexes on columns that appear in your WHERE clauses. There are a few exceptions to that rule:
If the column only has one or two unique values (the canonical example of this is "gender" - with only "Male" and "Female" the possible values, there is no point to an index here). Generally, you want an index that will be able to restrict the rows that need to be processed by a significant number (for example, an index that only reduces the search space by 50% is not worth it, but one that reduces it by 99% is).
If you are search for x LIKE '%something' then there is no point for an index. If you think of an index as specifying a particular order for rows, then sorting by x if you're searching for "%something" is useless: you're going to have to scan all rows anyway.
So let's take a look at the case where you're searching for "keyword 'accounting'". According to your result page, the SQL that this generates is:
SELECT
*
FROM (
SELECT TOP 10
ROW_NUMBER() OVER (ORDER BY sq.name) AS Row,
sq.*
FROM (
SELECT
c.*,
p.providername,
p.school,
p.website,
p.type
FROM
cpd_COURSES c, cpd_PROVIDERS p
WHERE
c.providerid = p.providerid AND
c.activatedYN = 'Y' AND
(
c.name like '%accounting%' OR
c.title like '%accounting%' OR
c.keywords like '%accounting%'
)
) sq
) AS temp
WHERE
Row >= 1 AND Row <= 10
In this case, I will assume that cpd_COURSES.providerid is a foreign key to cpd_PROVIDERS.providerid in which case you don't need an index, because it'll already have one.
Additionally, the activatedYN column is a T/F column and (according to my rule above about restricting the possible values by only 50%) a T/F column should not be indexed, either.
Finally, because searching with a x LIKE '%accounting%' query, you don't need an index on name, title or keywords either - because it would never be used.
So the main thing you need to do in this case is make sure that cpd_COURSES.providerid actually is a foreign key for cpd_PROVIDERS.providerid.
SQL Server Specific
Because you're using SQL Server, the Management Studio has a number of tools to help you decide where you need to put indexes. If you use the "Index Tuning Wizard" it is actually usually pretty good at tell you what will give you the good performance improvements. You just cut'n'paste your query into it, and it'll come back with recommendations for indexes to add.
You still need to be a little bit careful with the indexes that you add, because the more indexes you have, the slower INSERTs and UPDATEs will be. So sometimes you'll need to consolidate indexes, or just ignore them altogether if they don't give enough of a performance benefit. Some judgement is required.
Is this the real live database data? 52,000 records is a very small table, relatively speaking, for what SQL 2005 can deal with.
I wonder how much RAM is allocated to the SQL server, or what sort of disk the database is on. An IDE or even SATA hard disk can't give the same performance as a 15K RPM SAS disk, and it would be nice if there was sufficient RAM to cache the bulk of the frequently accessed data.
Having said all that, I feel the " (c.name like '%accounting%' OR c.title like '%accounting%' OR c.keywords like '%accounting%') " clause is problematic.
Could you create a separate Course_Keywords table, with two columns "courseid" and "keyword" (varchar(24) should be sufficient for the longest keyword?), with a composite clustered index on courseid+keyword
Then, to make the UI even more friendly, use AJAX to apply keyword validation & auto-completion when people type words into the keywords input field. This gives you the behind-the-scenes benefit of having an exact keyword to search for, removing the need for pattern-matching with the LIKE operator...
Using CF9? Try using Solr full text search instead of %xxx%?
You'll want to create indexes on the fields you search by. An index is a secondary list of your records presorted by the indexed fields.
Think of an old-fashioned printed yellow pages - if you want to look up a person by their last name, the phonebook is already sorted in that way - Last Name is the clustered index field. If you wanted to find phone numbers for people named Jennifer or the person with the phone number 867-5309, you'd have to search through every entry and it would take a long time. If there were an index in the back with all the phone numbers or first names listed in order along with the page in the phonebook that the person is listed, it would be a lot faster. These would be the unclustered indexes.
I would try changing your IN statements to an EXISTS query to see if you get better performance on the Zip code lookup. My experience is that IN statements work great for small lists but the larger they get, you get better performance out of EXISTS as the query engine will stop searching for a specific value the first instance it runs into.
<CFIF zipcodes is not "">
EXISTS (
SELECT zipcode
FROM cpd_CODES_ZIPCODES
WHERE zipcode = p.zipcode
AND 3963 * (ACOS((SIN(#getzipcodeinfo.latitude#/57.2958) * SIN(latitude/57.2958)) +
(COS(#getzipcodeinfo.latitude#/57.2958) * COS(latitude/57.2958) *
COS(longitude/57.2958 - #getzipcodeinfo.longitude#/57.2958)))) <= #radius#
)
</CFIF>

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