There are n location columns of various locations.
There's Token column at the end where each location row is associated with a different token.
TASK
Associate each token to each location column such that the relationship is named after the column name.
Example
My cypher code
load csv with headers from "file:///locations.csv" as row with row where row is not null
merge (l1:locations {name:row.LOC_1})
merge (t:tokens {name:row.Token})
merge (l1) -[:LOC_1]->(t)
As you can see, This code loads each column and relates them to tokens manually which is a tedious task. In reality, there are 67 columns and doing this manually takes a lot of time.
Hi,
This one works, but could somehow be optimized.
load csv with headers from "file:///locations.csv" as row with row
with row,keys(row) as columns
merge (token:tokens {name:row.Token})
with row,columns,token
unwind range(0,size(columns)) as columnIndex
with row,columns[columnIndex] as columnName,token
where not columnName='Token'
merge (l1:locations {name:row[columnName]})
with token,columnName,l1
call apoc.merge.relationship(token,columnName,null,null,l1,null)
yield rel
return count(rel)
Hey @filantrop,
Thanks for the code.
There are few things to consider,
1.There are null values in some columns. (Avoid them and load remaining values)
2. The dataset is too huge with 150K records and 67 columns. (How can we load faster)
(Also in original dataset the columns are named, c1,c2....cn)
Can you please modify your code keeping in mind the above points?
Test this one. You also could change the batch size of the transactions by uncommenting the //OF 500 rows
otherwise the defaultsize is 1000
:auto load csv with headers from "file:///locations.csv" as row with row
with row
call{
with row
with row,keys(row) as columns
merge (token:tokens {name:row.Token})
with row,columns,token
unwind range(0,size(columns)) as columnIndex
with row,columns[columnIndex] as columnName,token
where not columnName='Token' and not row[columnName] is null
merge (l1:locations {name:row[columnName]})
with token,columnName,l1
call apoc.merge.relationship(token,columnName,null,null,l1,null)
yield rel
return rel
} IN TRANSACTIONS //OF 500 ROWS
return count(rel)
5 minutes since I started running this code. It's still running, will keep you updated here about the progress.
Also, it ran out of memory when I ran the first code in Neo4J Aura. Now I'm running it locally, hope this works faster. Any other tweaks I should do if this also runs out of memory?
After 45 minutes, it finally completed running and works well.
Also, I am a beginner and still learning about Neo4J. I appreciate it if you suggest any important concepts for me to learn this software quickly.
Thank you so much!