I am trying to load large dataset into neo4j-3 and looking for the options. I found one neo4j-import but the problem with that is it is for initial load only. I have to load 2M records around every week.
I tried loading through shell but having some performance issue, I tried following.
1) Creating constraint upfront.
2) Creating Node and relationships in separate query.
3) Heap space 8G
4) dbms.memory.pagecache 4G
Many times the import just hangs and does nothing for hours.
Edit - CSV load being executed:
USING PERIODIC COMMIT 5000
LOAD CSV WITH HEADERS
FROM "file:///my_sds_39_joe.csv"
AS row
OPTIONAL MATCH (per:Person {UID : "Person."+row.player_cardnum})
WHERE per IS NULL
MERGE (p:Person {CardNumber : row.player_cardnum})
ON CREATE SET p.Creation Date = timestamp(), p.Modification Date = timestamp() ;
EDIT
On a second look, seems like you're trying to implement some kind of conditional logic to your insert.
It looks like what you're trying to do is figure out if a :Person exists with a UID (derived from some concatenation with row.player_cardnum), and in the case where that :Person doesn't exist and the match fails, MERGE a :Person with the CardNumber given by row.player_cardnum.
If this is your goal, you're ALMOST there with your query. The problem is with your WHERE clause.
Understand that WHERE clauses are linked with a preceding MATCH, OPTIONAL MATCH, or WITH, and only affects the linked clause.
With that WHERE on that OPTIONAL MATCH, per will always be null, but more importantly, your row will still exist, and the following MERGE will ALWAYS take place for all rows in the CSV. This is probably the source of your slowdown, as it's creating new :Person nodes for all rows.
If you're trying to null out the row completely when the OPTIONAL MATCH hits on an existing :Person (so the MERGE won't happen in that case), you'll need to add a WITH clause, and make sure your WHERE clause is applied to it instead of the OPTIONAL MATCH.
Additionally, make sure that you have either unique constraints or indexes on Person.UID and Person.CardNumber. As for the UID match, I've heard that indexes are not used when there's some kind of string concatenation of the thing you're matching upon, so you may need to assemble it first and pass it in with a WITH.
Your final query would look like this:
USING PERIODIC COMMIT 5000
LOAD CSV WITH HEADERS
FROM "file:///my_sds_39_joe.csv"
AS row
// first build the UID so we can take advantage of the index
WITH row, "Person." + row.player_cardnum AS UID
OPTIONAL MATCH (per:Person {UID : UID})
// the WHERE now applies to the WITH, which will filter out and null out the row when an OPTIONAL MATCH is found
WITH row, per
WHERE per IS NULL
MERGE (p:Person {CardNumber : row.player_cardnum})
ON CREATE SET p.Creation Date = timestamp(), p.Modification Date = timestamp() ;
Related
I am loading simple csv data into neo4j. The data is simple as follows :-
uniqueId compound value category
ACT12_M_609 mesulfen 21 carbon
ACT12_M_609 MNAF 23 carbon
ACT12_M_609 nifluridide 20 suphate
ACT12_M_609 sulfur 23 carbon
I am loading the data from the URL using the following query -
LOAD CSV WITH HEADERS
FROM "url"
AS row
MERGE( t: Transaction { transactionId: row.uniqueId })
MERGE(c:Compound {name: row.compound})
MERGE (t)-[r:CONTAINS]->(c)
ON CREATE SET c.category= row.category
ON CREATE SET r.price =row.value
Next I do the aggregation to count total orders for a compound and create property for a node in the following way -
MATCH (c:Compound) <-[:CONTAINS]- (t:Transaction)
with c.name as name, count( distinct t.transactionId) as ord
set c.orders = ord
So far so good. I can accomplish what I want but I have the following 2 questions -
How can I create the orders property for compound node in the first step itself? .i.e. when I am loading the data I would like to perform the aggregation straight away.
For a compound node I am also setting the property for category. Theoretically, it can also be modelled as category -contains-> compound by creating Categorynode. But what advantage will I have if I do it? Because I can execute the queries and get the expected output without creating this additional node.
Thank you for your answer.
I don't think that's possible, LOAD CSV goes over one row at a time, so at row 1, it doesn't know how many more rows will follow.
I guess you could create virtual nodes and relationships, aggregate those and then use those to create the real nodes, but that would be way more complicated. Virtual Nodes/Rels
That depends on the questions/queries you want to ask.
A graph database is optimised for following relationships, so if you often do a query where the category is a criteria (e.g. MATCH (c: Category {category_id: 12})-[r]-(:Compound) ), it might be more performant to create a label for it.
If you just want to get the category in the results (e.g. RETURN compound.category), then it's fine as a property.
we are trying to run a cypher query but we are not able to get the results we want.
It is important to note that we cannot make this work with subqueries because we are using Neo4j 3.5 and in this version, they are still not available.
The problem is that we have two parts for a query, the first one will fix the variables for the second part, and the second part consists of multiple matches, and it has to get the results of the previous query and if at least one of the matches return a result for a row, this row is not filtered out, else if none return result it is discarded.
More specifically, the query we are trying to run is similar to the following one:
//First part of the query where we want to fix variables with the match and where
MATCH (u:User)-[:ASSIGNED_TO]->(t:Task)-[:PENDING]->(ob:Object)<-[:HAS_OPEN_OBJECT]-(do:DataObject)<-[:ASOCIATED]-(:Module)-[:CAN_LIST]->(view:WidgetObject)
WHERE u.uid = 'user_uid'
AND view.uid = 'view_uid'
AND view.object_name = do.object_type
with do, t, ob
// In this second part of the query we want to maintain the variables of the previous part and if at least one matches the value should be returned
// we have tried with UNION but we will need pagination, but even with union it's not working
MATCH (ac:Action)<-[:ASOCIATED]-(t)-[rel:COMPLETED|PENDING]->(ob)<-[:HAS_OPEN_OBJECT|HAS_CLOSED_OBJECT]-(do)
WHERE ac.name CONTAINS 'body'
WITH COLLECT({data_object_uid: do.uid}) as act_filter
MATCH (c:Comment)<-[:COMMENTED]-(t)-[rel:COMPLETED|PENDING]->(ob)<-[:HAS_OPEN_OBJECT|HAS_CLOSED_OBJECT]-(do)
WHERE c.body CONTAINS 'body'
WITH act_filter + COLLECT({data_object_uid: do.uid}) as comment_filter
MATCH (at:Attachment)<-[:HAS_ATTACHMENT]-(t)-[rel:COMPLETED|PENDING]->(ob)<-[:HAS_OPEN_OBJECT|HAS_CLOSED_OBJECT]-(do)
WHERE at.name CONTAINS 'body'
WITH comment_filter + COLLECT({data_object_uid: do.uid}) as attachment_filter
UNWIND attachment_filter as row
return row.data_object_uid
We are not sure if in the second part, the second and third matches are maintaining the same subset of results coming from the first part of the query.
A funny behavior we have found is that if we remove the last match we are getting results but if we add it, we are not getting any results. We do not understand this behavior because if the second match is returning results and they are stored in a variable after a collect, appending this to the next collected results should return something.
For example, if the second match returns as comment_filter [{data_object_uid: "343dienmd3-dasd"}] and the third match is not returning anything, after the concatenation in the WITH clause it should return the same thing, but the result is empty.
We need some light here, we don't know if we are close and we are making a stupid mistake or we are getting all wrong and we need to change the approach completely.
Since you do not know which of the three matches in the second part will yield results, I would try something along the lines below:
NOTE I used ASSOCIATED instead of ASOCIATED
MATCH (n)<-[:ASSOCIATED|COMMENTED|HAS_ATTACHMENT]-(t)-[rel:COMPLETED|PENDING]->(ob)<-[:HAS_OPEN_OBJECT|HAS_CLOSED_OBJECT]-(do)
WHERE
(n:Action AND n.name CONTAINS 'body')
OR
(n:Comment AND n.body CONTAINS 'body')
OR
(n:Attachment AND n.name CONTAINS 'body')
RETURN COLLECT(DISTINCT {data_object_uid: do.uid})
I have 2 csv files which I am trying to load into a Neo4j database using cypher: drivers.csv which holds every formula 1 driver and lap times.csv which stores every lap ever raced in F1.
I have managed to load in all of the nodes, although the lap times file is very large so it took quite a long time! I then tried to add relationships after, but there is so many that needs to be added that I gave up on it waiting (it was taking multiple days and still had not loaded in fully).
I’m pretty sure there is a way to load in the nodes and relationships at the same time, which would allow me to use periodic commit for the relationships which I cannot do right now. Essentially I just need to combine the 2 commands into one and after some attempts I can’t seem to work out how to do it?
// load in the lap_times.csv, changing the variable names - about half million nodes (takes 3-4 days)
PERIODIC COMMIT 25000
LOAD CSV WITH HEADERS from 'file:///lap_times.csv'
AS row
MERGE (lt: lapTimes {raceId: row.raceId, driverId: row.driverId, lap: row.lap, position: row.position, time: row.time, milliseconds: row.milliseconds})
RETURN lt;
// add a relationship between laptimes, drivers and races - takes 3-4 days
MATCH (lt:lapTimes),(d:Driver),(r:race)
WHERE lt.raceId = r.raceId AND lt.driverId = d.driverId
MERGE (d)-[rel8:LAPPING_AT]->(lt)
MERGE (r)-[rel9:TIMED_LAP]->(lt)
RETURN type(rel8), type(rel9)
Thanks in advance for any help!
You should review the documentation for indexes here:
https://neo4j.com/docs/cypher-manual/current/administration/indexes-for-search-performance/
Basically, indexes, once created, allow quick lookups of nodes of a given label, for the given property or properties. If you DON'T have an index and you do a MATCH or MERGE of a node, then for every row of that MATCH or MERGE, it has to do a label scan of all nodes of the given label and check all of their properties to find the nodes, and that becomes very expensive, especially when loading CSVs because those operations are likely happening for each row in the CSV.
For your :lapTimes nodes (though we would recommend you use singular labels in most cases), if there are none of them in your graph to start with, then a CREATE instead of a MERGE is fine. You may want a composite index on :lapTimes(raceId, driverId, lap), since that should uniquely identify the node, if you need to look it up later. Using CREATE instead of MERGE here should process much much faster.
Your second query should be MATCHing on :lapTimes nodes (label scan), and from each doing an index lookup on the :race and :driver nodes, so indexes are key here for performance.
You need indexes on: :race(raceId) and :Driver(driverId).
MATCH (lt:lapTimes)
WITH lt, lt.raceId as raceId, lt.driverId as driverId
MATCH (d:Driver), (r:race)
WHERE r.raceId = raceId AND d.driverId = driverId
MERGE (d)-[:LAPPING_AT]->(lt)
MERGE (r)-[:TIMED_LAP]->(lt)
You might consider CREATE instead of MERGE for the relationships, if you know there are no duplicate entries.
I removed your RETURN because returning the types isn't useful information.
Also, consider using consistent cases for your node labels, and that you are using the same case between the labels in your graph and the indexes you create.
Also, you would probably want to batch these changes instead of trying to process them all at once.
If you install APOC Procedures you can make use of apoc.periodic.iterate(), which can be used to batch changes, which will be faster and easier on your heap. You will still need indexes first.
CALL apoc.periodic.iterate("
MATCH (lt:lapTimes)
WITH lt, lt.raceId as raceId, lt.driverId as driverId
MATCH (d:Driver), (r:race)
WHERE r.raceId = raceId AND d.driverId = driverId
RETURN lt, d, ir",
"MERGE (d)-[:LAPPING_AT]->(lt)
MERGE (r)-[:TIMED_LAP]->(lt)", {}) YIELD batches, total, errorMessages
RETURN batches, total, errorMessages
Single CSV load
If you want to handle everything all at once in a single CSV load, you can do that, but again you will need indexes first. Here's what you'll need at a minimum:
CREATE INDEX ON :Driver(driverId);
CREATE INDEX ON :Race(raceId);
After those are created, you can use this, assuming you are starting from scratch (I fixed the case of your labels and made them singular:
USING PERIODIC COMMIT 25000
LOAD CSV WITH HEADERS from 'file:///lap_times.csv' AS row
MERGE (d:Driver {driverId:row.driverId})
MERGE (r:Race {raceId:row.raceId})
CREATE (lt:LapTime {raceId: row.raceId, driverId: row.driverId, lap: row.lap, position: row.position, time: row.time, milliseconds: row.milliseconds})
CREATE (d)-[:LAPPING_AT]->(lt)
CREATE (r)-[:TIMED_LAP]->(lt)
I'm trying to load some data into neo4j from csv files, and it seems a unique constraint error is triggered when it shouldn't. In particular, I created a contraint using
CREATE CONSTRAINT ON (node:`researcher`) ASSERT node.`id_patstats` IS UNIQUE;
Then, after inserting some data in neo4j, if I run (in neo4j browser)
MATCH (n:researcher {id_patstats: "2789"})
RETURN n
I get no results (no changes, no records), but if I run
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM
'file:///home/manu/proyectos/PTL_RDIgraphs/rdigraphs/datamanager/tmp_patents/person906.csv' AS line
MERGE (n:researcher {`name` : line.`person_name`})
SET n.`id_patstats` = line.`person_id`;
I get
Neo.ClientError.Schema.ConstraintValidationFailed: Node(324016)
already exists with label researcher and property id_patstats =
'2789'
and the content of file person906.csv is
manu#cochi tmp_patents $cat person906.csv
person_id,person_name,doc_std_name,doc_std_name_id
2789,"li, jian",LI JIAN,2390
(this a minimum non working example extracted from a larger dataset; also, in the original "person906.csv" I made sure that "id_patstats" is really unique).
Any clue?
EDIT:
Still struggling with this...
If I run
MATCH (n)
WHERE EXISTS(n.id_patstats)
RETURN DISTINCT "node" as entity, n.id_patstats AS id_patstats
LIMIT 25
UNION ALL
MATCH ()-[r]-()
WHERE EXISTS(r.id_patstats)
RETURN DISTINCT "relationship" AS entity, r.id_patstats AS id_patstats
LIMIT 25
(clicking in the neo4j browser to get some examples of the id_patstats property) I get
(no changes, no records)
that is, id_patstats property is not set anywhere. Moreover
MATCH (n:researcher {`name` : "li, jian"})
SET n.`id_patstats` = XXX;
this will always trigger an error regardless of XXX, which (I guess) means the actual problem is that the name "li, jian" is already present. Although I didn't set any constraint on the name property, I'm guessing neo4j goes like this: you are trying to set a UNIQUE property on a node matching a property (name) that is not necessarily UNIQUE; hence that match could yield several nodes and I can't set the same UNIQUE property on all of them...so I won't even try
At least two of your researchers have the same name. You shouldn't MERGE by name and then add id as a property. You should MERGE by id and add the name as a property and it will work fine.
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM
'file:///home/manu/proyectos/PTL_RDIgraphs/rdigraphs/datamanager/tmp_patents/person906.csv' AS line
MERGE (n:researcher {`id_patstats`:line.`person_id`})
SET n.name`=line.`person_name`;
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:///dept_emp.csv" AS row
MATCH (emp_no:Employee {emp_no: row.emp_no})
MATCH (dept_no:departments {dept_no: row.dept_no})
MERGE(Employee)-[:belongs_to{from_date: row.from_date,to_date:
row.to_date}]->(departments);
i want to make a relationship with properties using this query the structure of node
employee is
[
gender M
emp_no 10001
birth_date 1953-09-02
last_name Facello
hire_date 1986-06-26
first_name Georgi
]
node departements is
[
dept_no d009
dept_name Customer Service
]
structure of file
dept_emp.csv is
(
emp_no dept_name from_date to_date
)
the ide does'nt showing an error just start processing and after 6 hour still processing.
I think you may be a bit confused about match syntax, for which part is the variable, and which is the node label.
MATCH (emp_no:Employee {emp_no: row.emp_no})
In the above match, :Employee is the label of the node. emp_no is the variable bound to the :Employee node that is matched.
Later in the query, you have this:
MERGE(Employee)-[:belongs_to{from_date: row.from_date,to_date:
row.to_date}]->(departments);
The problem here is that Employee and departments don't refer to anything you've matched to previously, this is the first occurrence of these variables, and that will throw off what this MERGE is doing. As it is, it is checking all relationships between all nodes (and doing this for every row in your CSV), looking for :belongs_to relationships with the given date properties.
I suggest you stop the query (by killing Neo4j if necessary) cleaning up the data (in case it needs it) and trying again, but try a MERGE with the variables you previously bound:
MERGE(emp_no)-[:belongs_to{from_date: row.from_date,to_date:
row.to_date}]->(dept_no);
Make sure you have indexes or unique constraints on :Employee(emp_no) and :departments(dept_no) for fast matching.