I have a CSV file containing the data that I want to convert into a graph database using Neo4j. The Columns in the file are in the following format :
Person1 | Person2 | Points
Now the ids in Person1 and Person2 are redundant , so I am using a Merge statement instead. But I am not getting the correct results.
For a sample dataset , the output seems to be correct , but when I import my dataset consisting of 2M rows, it somehow doesn't create the relationships.
I am putting the cypher code that I am using currently.
USING PERIODIC COMMIT 1000
LOAD CSV WITH HEADERS FROM "file:C:/Users/yogi/Documents/Neo4j/default.graphdb/sample.csv" AS csvline
MERGE (p1:Person {id:toInt(csvline.id1)})
MERGE (p2:Person {id:toInt(csvline.id2)})
CREATE (p1)-[:points{count:toInt(csvline.c)}]->(p2)
Some things you should check:
are you using an index: CREATE INDEX ON :Person(id) should be run before the import
depending on the Neo4j version you're using, the statement might be subject to "eager-pipe" which basically prevents the periodic commit. For more on eager pipe, see http://www.markhneedham.com/blog/2014/10/23/neo4j-cypher-avoiding-the-eager/
Related
(First time posting so please bear with) I have two different dataframes, one of which contains a column of replacement data for a selection of data within the first dataframe.
#dataframe 1
df<-data.frame(site= rep(1:4,3), landings = rep("val",12),
harbour = c("a","b","c","d","e","f","g","h","i","j","k","l"))
#dataframe 2
new_site4<-data.frame(harbour = c("a","b","c","d","e","f","g","h","i","j","k","l"),
sub_site = c("x","x","y","x","y","y","y","x","y","x","y","y") )
I want to replace the "site" in dataframe 1 with the "subsite" in dataframe 2 based on the match of "harbour" however I only need to do it for records for site "4".
Is there a neat way to select only site 4 and then replace the site number with the subsite, ideally without merging or without creating a whole new dataframe. My real dataset is large but the key is only small as it only refers to a small selection of the data which needs the subsite added.
I tried using match() on my main dataset but for some reason it only matched some of the required data not all of it, but this code wont work on my sample data either.
#df$site[match(df$harbour, new_site4$harbour)] <- new_site4$sub_site[match(df$harbour, df$harbour)]`
I have this JSON on a Bucket that has been crawled with a classifier that splits arrays into record with this JSON classifier $[*].
I noticed that the JSON is on a single line - nothing wrong with syntax - but this results in the table being created having a single column of type array containing a struct which contains the actual fields I need.
In Athena I wasn't able to access the data and Glue was not able to read the columns as in array.field; so I manually changed the structure of the table making a single struct type with the other fields inside. This I'm able to query on Athena and get the Glue wizard to recognise the single columns as part of the struct.
When I create the job and map the fields accordingly (this is what is automatically generated, note the array.field notation applymapping1 = ApplyMapping.apply(frame = datasource0, mappings = [("array.col1", "long", "col1", "long"), ("array.col2", "string", "col2", "string"), ("array.col3", "string", "col3", "string")], transformation_ctx = "applymapping1")) I test the output on a table in an S3 Bucket. The Job does not fail at all, BUT creates files in the Bucket that are empty!
Another thing I've tried is to modify the Source JSON and add return lines:
this is before:
[{"col1":322,"col2":299,"col3":1613552400000,"col4":"TEST","col5":"TEST"},{"col1":2,"col2":0,"col3":1613552400000,"col4":"TEST","col5":"TEST"}]
this is after:
[
{"col1":322,"col2":299,"col3":1613552400000,"col4":"TEST","col5":"TEST"},
{"col1":2,"col2":0,"col3":1613552400000,"col4":"TEST","col5":"TEST"}
]
Having the file modified as stated before lets me correctly read and write data; this led me to believe that the problem is having a bad JSON at the beginning. Before asking to change the JSON is there something I can implement in my Glue Job (Spark 2.4, Python 3) to handle a JSON on a single line? I've searched everywhere but found nothing.
The end goal is to load data into Redshift, we're working S3 to S3 to check on why data isn't being read.
Thanks in advance for your time and consideration.
I could need some help with a Anylogic Model.
Model (short): Manufacturing scenario with orders move in a individual route. The workplaces (WP) are dynamical created by simulation start. Their names, quantity and other parameters are stored in a database (excel Import). Also the orders are created according to an import. The Agent population "order" has a collection routing which contains the Workplaces it has to stop in the specific order.
Target: I want a moveTo block in main which finds the next destination of the agent order.
Problem and solution paths:
I set the destination Type to agent and in the Agent field I typed a function agent.getDestination(). This function is in order which returns the next entry of the collection WP destinationName = routing.get(i). With this I get a Datatype error (while run not compiling). I quess it's because the database does not save the entrys as WP Type but only String.
Is there a possiblity to create a collection with agents from an Excel?
After this I tried to use the same getDestination as String an so find via findFirst the WP matching the returned name and return it as WP. WP targetWP = findFirst(wps, w->w.name == destinationName);
Of corse wps (the population of Workplaces) couldn't be found.
How can I search the population?
Maybe with an Agentlink?
I think it is not that difficult but can't find an answer or a solution. As you can tell I'm a beginner... Hope the description is good an someone can help me or give me a hint :)
Thanks
Is there a possiblity to create a collection with agents from an Excel?
Not directly using the collection's properties and, as you've seen, you can't have database (DB) column types which are agent types.1
But this is relatively simple to do directly via Java code (and you can use the Insert Database Query wizard to construct the skeleton code for you).
After this I tried to use the same getDestination as String an so find via findFirst the WP matching the returned name and return it as WP
Yes, this is one approach. If your order details are in Excel/the database, they are presumably referring to workplaces via some String ID (which will be a parameter of the workplace agents you've created from a separate Excel worksheet/database table). You need to use the Java equals method to compare strings though, not == (which is for comparing numbers or whether two objects are the same object).
I want a moveTo block in main which finds the next destination of the agent order
So the general overall solution is
Create a population of Workplace agents (let's say called workplaces in Main) from the DB, each with a String parameter id or similar mapped from a DB column.
Create a population of Order agents (let's say called orders in Main) from the DB and then, in their on-startup action, set up their collection of workplace IDs (type ArrayList, element class String; let's say called workplaceIDsList) using data from another DB table.
Order probably also needs a working variable storing the next index in the list that it needs to go to (so let's say an int variable nextWorkplaceIndex which starts at 0).
Write a function in Main called getWorkplaceByID that has a single String argument id and returns a Workplace. This gets the workplace from the population that matches the ID; a one-line way similar to yours is findFirst(workplaces, w -> w.id.equals(id)).
The MoveTo block (which I presume is in Main) needs to move the Order to an agent defined by getWorkplaceByID(agent.workplaceIDsList.get(nextWorkplaceIndex++)). (The ++ bit increments the index after evaluating the expression so it is ready for the next workplace to go to.)
For populating the collection, you'd have two tables, something like the below (assuming using strings as IDs for workplaces and orders):
orders table: columns for parameters of your orders (including some String id column) other than the workplace-list. (Create one Order agent per row.)
order_workplaces table: columns order_id, sequence_num and workplace_id (so with multiple rows specifying the sequence of workplace IDs for an order ID).
In the On startup action of Order, set up the skeleton query code via the Insert Database Query wizard as below (where we want to loop through all rows for this order's ID and do something --- we'll change the skeleton code to add entries to the collection instead of just printing stuff via traceln like the skeleton code does).
Then we edit the skeleton code to look like the below. (Note we add an orderBy clause to the initial query so we ensure we get the rows in ascending sequence number order.)
List<Tuple> rows = selectFrom(order_workplaces)
.where(order_workplaces.order_id.eq(id))
.orderBy(order_workplaces.sequence_num.asc())
.list();
for (Tuple row : rows) {
workplaceIDsList.add(row.get(order_workplaces.workplace_id));
}
1 The AnyLogic database is a normal relational database --- HSQLDB in fact --- and databases only understand their own specific data types like VARCHAR, with AnyLogic and the libraries it uses translating these to Java types like String. In the user interface, AnyLogic makes it look like you set the column types as int, String, etc. but these are really the Java types that the columns' contents will ultimately be translated into.
AnyLogic does support columns which have option list types (and the special Code type column for columns containing executable Java code) but these are special cases using special logic under the covers to translate the column data (which is ultimately still a string of characters) into the appropriate option list instance or (for Code columns) into compiled-on-the-fly-and-then-executed Java).
Welcome to Stack Overflow :) To create a Population via Excel Import you have to create a method and call Code like this. You also need an empty Population.
int n = excelFile.getLastRowNum(YOUR_SHEET_NAME);
for(int i = FIRST_ROW; i <= n; i++){
String name = excelFile.getCellStringValue(YOUR_SHEET_NAME, i, 1);
double SEC_PARAMETER_TO_READ= excelFile.getCellNumericValue(YOUR_SHEET_NAME, i, 2);
WP workplace = add_wps(name, SEC_PARAMETER_TO_READ);
}
Now if you want to get a workplace by name, you have to create a method similar to your try.
Functionbody:
WP workplaceToFind = wps.findFirst(w -> w.name.equals(destinationName));
if(workplaceToFind != null){
//do what ever you want
}
I am trying to initiate a relationship between two columns in Neo4j. my dataset is a CSV file with two-column refers to Co-Authorship and I want to Construct a Network of it. I already load the data, return them and match them.
Loading
load csv from 'file:///conet1.csv' as rec
return the data
create (:Guys {source: rec[0], target: rec[1]})
now I need to Construct the Collaboration Network of data by making a relationship between source and target columns. What do you propose for the purpose?
I was able to make a relationship between mentioned columns in NetworkX graph libray in python like this:
import pandas as pd
import networkx as nx
g = nx.Graph()
df = pd.read_excel('Colab.csv', columns= ['source', 'target'])
g = nx.from_pandas_edgelist(df,'source','target', 'weight')
If I understand your use case, I do not believe you should be creating Guys nodes just to store relationship info. Instead, the graph-oriented approach would be to create an Author node for each author and a relationship (say, of type COLLABORATED_WITH) between the co-authors.
This might work for you, or at least give you a clue:
LOAD CSV FROM 'file:///conet1.csv' AS rec
MERGE (source:Author {id: rec[0]})
MERGE (target:Author {id: rec[1]})
CREATE (source)-[:COLLABORATED_WITH]->(target)
If it is possible that the same relationship could be re-created, you should replace the CREATE with a more expensive MERGE. Also, a work can have any number of co-authors, so having a relationship between every pair may be sub-optimal depending on what you are trying to do; but that is a separate issue.
I search for a query which is pretty similar to this one. But as an extension, I do not want to count all objects, but just over the ones, that are fairly recent.
In my case, there are two models. Let one be the Source and one be the Data. As result I'd like to get a list of all Sources ordered by the number of data records, that has been collected during the last week.
For me it is not iteresting, how many data records have been collected in total, but if there is a recent activity of that source.
Using the following code snippet from the above link, I cannot make up how to subquery the Data Table before.
from django.db.models import Count
activity_per_source = Source.objects.annotate(count_data_records=Count('Data')) \
.order_by('-count_data_records')
The only ways I came up with, would be to write native SQL or to process this in a loop and individual queries. Is there a Django-Query version?
(I use a MySQL database and Django 1.5.4)
Checkout out the docs on the order of annotate and filter: https://docs.djangoproject.com/en/1.5/topics/db/aggregation/#order-of-annotate-and-filter-clauses
Try something along the lines of:
activity_per_source = Source.objects.\
filter(data__date__gte=one_week_ago).\
annotate(count_data_records=Count('Data')).\
order_by('-count_data_records').distinct()
There is a way of doing that mixing Django queries with SQL via extra:
start_date = datetime.date.today() - 7
activity_per_source = (
Source.objects
.extra(where=["(select max(date) from app_data where source_id=app_source.id) >= '%s'"
% start_date.strftime('%Y-%m-%d')])
.annotate(count_data_records=Count('Data'))
.order_by('-count_data_records'))
The where part will filter the Sources by its Data last date.
Note: replace table and field names with actual ones.