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Description
Querying and Managing 'Neo4J' Databases in 'R'
Sends queries to a specified 'Neo4J' graph database, capturing results in a dataframe where appropriate. Other useful functions for the importing and management of data on the 'Neo4J' server and basic local server admin.

neo4jshell

Lifecycle:experimental CRANstatus TotalDownloads R buildstatus Travis buildstatus

The goal of neo4jshell is to provide rapid querying of ‘Neo4J’ graph databases by offering a programmatic interface with ‘cypher-shell’. A wide variety of other functions are offered that allow importing and management of data files for local and remote servers, as well as simple administration of local servers for development purposes.

Pre-installation notes

This package requires the ssh package for interacting with remote ‘Neo4J’ databases, which requires libssh to be installed. See the vignettes for the ssh package here for more details.

This package also requires the ‘cypher-shell’ executable to be available locally. This is installed as standard in ‘Neo4J’ installations and can usually be found in the bin directory of that installation. It can also be installed standalone using Homebrew or is available here: https://github.com/neo4j/cypher-shell.

It is recommended, for ease of use, that the path to the ‘cypher-shell’ executable is added to your PATH environment variable. If not, you should record its location for use in some of the functions within this package.

Installation

You can install the released version of neo4jshell from CRAN with:

install.packages("neo4jshell")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("keithmcnulty/neo4jshell")

Functionality

Query

neo4j_query() sends queries to the specified ‘Neo4J’ graph database and, where appropriate, retrieves the results in a dataframe.

In this example, the movies dataset has been started locally in the ‘Neo4J’ browser, with a user created that has the credentials indicated. cypher-shell is in the local system path.

library(neo4jshell)
library(dplyr)
library(tibble)
# set credentials (no port required in bolt address)
neo_movies <- list(address = "bolt://localhost", uid = "neo4j", pwd = "password")

# find directors of movies with Kevin Bacon as actor
CQL <- 'MATCH (p1:Person {name: "Kevin Bacon"})-[:ACTED_IN]->(m:Movie)<-[:DIRECTED]-(p2:Person)
RETURN p2.name, m.title;'

# run query
neo4j_query(con = neo_movies, qry = CQL)
#>      p2.name        m.title
#> 1 Ron Howard    Frost/Nixon
#> 2 Rob Reiner A Few Good Men
#> 3 Ron Howard      Apollo 13

Older versions of ‘Neo4J’ and ‘cypher-shell’ (<4.0) will require the encryption argument to be explicitly 'true' or 'false'. For newer versions, which have multi-tenancy, you can use the database argument to specify the database to query.

Server management

  • neo4j_import() imports a csv, zip or tar.gz file from a local source into the specified ‘Neo4J’ import directory, uncompresses compressed files and removes the original compressed file as clean up.
  • neo4j_rmfiles() removes specified files from specified ‘Neo4J’ import directory
  • neo4j_rmdir() removes entire specified subdirectories from specified ‘Neo4J’ import directory

Remote development

In this general example, we can see how these functions can be used for smooth ETL to a remote ‘Neo4J’ server. This example assumes that the URL of the server that hosts the ‘Neo4J’ database is the same as the bolt URL for the ‘Neo4J’ database. If not, a different set of credentials will be needed for using neo4j_import().

# credentials (note no port required in server address)
neo_server <- list(address = "bolt://neo.server.address", uid = "neo4j", pwd = "password")

# csv data file to be loaded onto 'Neo4J' server (path relative to current working directory)
datafile <- "data.csv"

# CQL query to write data from datafile to 'Neo4J'
loadcsv_CQL <- "LOAD CSV FROM 'file:///data.csv' etc etc;"

# path to import directory on remote 'Neo4J' server (should be relative to user home directory on remote server)
impdir <- "./import"

# import data
neo4jshell::neo4j_import(con = neo_server, source = datafile, import_dir = impdir)

# write data to 'Neo4J' (assumes cypher-shell is in system PATH variable)
neo4jshell:neo4j_query(con = neo_server, qry = loadcsv_CQL)

# remove data file as clean-up
neo4jshell::neo4j_rmfiles(con = neo_server, files = datafile, import_dir = impdir)

In Windows, the ‘cypher-shell’ executable may need to be specified with the file extension, for example shell_path = "cypher-shell.bat".

Local Development

If you are working with the ‘Neo4J’ server locally, below will help you get started.

First, the code below is relative to user and is using ‘Neo4J 4.0.4 Community’ installed at my user’s root. The directory containing the ‘cypher-shell’ and ‘neo4j’ executables are in my system’s PATH environment variables.

## start the local server
neo4j_start()
#> Directories in use:
#>   home:         /Users/keithmcnulty/neo4j-community-4.0.4
#>   config:       /Users/keithmcnulty/neo4j-community-4.0.4/conf
#>   logs:         /Users/keithmcnulty/neo4j-community-4.0.4/logs
#>   plugins:      /Users/keithmcnulty/neo4j-community-4.0.4/plugins
#>   import:       /Users/keithmcnulty/neo4j-community-4.0.4/import
#>   data:         /Users/keithmcnulty/neo4j-community-4.0.4/data
#>   certificates: /Users/keithmcnulty/neo4j-community-4.0.4/certificates
#>   run:          /Users/keithmcnulty/neo4j-community-4.0.4/run
#> Neo4j is already running (pid 2103).
#> [1] 0

## setup connection credentials and import directory location
neo_con <- list(address = "bolt://localhost:7687", uid = "neo4j", pwd = "password")
import_loc <- path.expand("~/neo4j-community-4.0.4/import/")

First we save mtcars to a .csv file, and we compress that file. This package supports a number of delivery formats, but we use a .zip file as an example.

mtcars <- mtcars %>% 
  tibble::rownames_to_column(var = "model")

write.csv(mtcars, "mtcars.csv", row.names = FALSE)
zip("mtcars.zip", "mtcars.csv")

Now we use neo4j_import() to place a copy of this file within the import directory you defined in import_loc above.

neo4j_import(local = TRUE, graph, source = "mtcars.zip", import_dir = import_loc)
#> Import and unzip successful!  Zip file has been removed!

We now write a CQL query to write some information from mtcars.csv to the graph, and execute that query.

CQL <- "LOAD CSV WITH HEADERS FROM 'file:///mtcars.csv' AS row
WITH row WHERE row.model IS NOT NULL
MERGE (c:Car {name: row.model});"

neo4j_query(neo_con, CQL)
#> Query succeeded with a zero length response from Neo4J

Now, let’s remove the mtcars.csv file from the import directory of our local server as cleanup. If you want to use a sub-directory to help manage your files during an ETL into ‘Neo4J’, you can remove that local sub-directory when your process has completed using neo4j_rmdir().

## remove the file
neo4j_rmfiles(local = TRUE, graph, files="mtcars.csv", import_dir = import_loc)
#> Files removed successfully!

Now let’s run a query to check the data was loaded to the graph.

CQL <- "MATCH (c:Car) RETURN c.name as name LIMIT 5;"

neo4j_query(neo_con, CQL)
#>                name
#> 1         Mazda RX4
#> 2     Mazda RX4 Wag
#> 3        Datsun 710
#> 4    Hornet 4 Drive
#> 5 Hornet Sportabout

Local server administration and control

  • neo4j_start() starts a local ‘Neo4J’ instance
  • neo4j_stop() stops a local ‘Neo4J’ instance
  • neo4j_restart() restarts a local ‘Neo4J’ instance
  • neo4j_status() returns the status of a local ‘Neo4J’ instance
  • neo4j_wipe() wipes an entire graph from a local ‘Neo4J’ instance

For example:


# my server was already running, confirm
neo4j_status()
#> Neo4j is running at pid 2103
#> [1] 0

# stop the server
neo4j_stop()
#> Stopping Neo4j....... stopped
#> [1] 0

# restart
neo4j_start()
#> Directories in use:
#>   home:         /Users/keithmcnulty/neo4j-community-4.0.4
#>   config:       /Users/keithmcnulty/neo4j-community-4.0.4/conf
#>   logs:         /Users/keithmcnulty/neo4j-community-4.0.4/logs
#>   plugins:      /Users/keithmcnulty/neo4j-community-4.0.4/plugins
#>   import:       /Users/keithmcnulty/neo4j-community-4.0.4/import
#>   data:         /Users/keithmcnulty/neo4j-community-4.0.4/data
#>   certificates: /Users/keithmcnulty/neo4j-community-4.0.4/certificates
#>   run:          /Users/keithmcnulty/neo4j-community-4.0.4/run
#> Starting Neo4j.
#> Started neo4j (pid 12838). It is available at http://localhost:7474/
#> There may be a short delay until the server is ready.
#> See /Users/keithmcnulty/neo4j-community-4.0.4/logs/neo4j.log for current status.
#> [1] 0

# give it a few seconds to fire up
Sys.sleep(10)

# query again
neo4j_query(neo_con, qry="MATCH (c:Car) RETURN c.name as name LIMIT 5;")
#>                name
#> 1         Mazda RX4
#> 2     Mazda RX4 Wag
#> 3        Datsun 710
#> 4    Hornet 4 Drive
#> 5 Hornet Sportabout

If you are using an admin account and you are using ‘Neo4J 4+’ you can check what databases are available by querying the system database.

neo4j_query(neo_con, qry="SHOW DATABASES;", database = "system")
#>     name        address       role requestedStatus currentStatus error default
#> 1  neo4j localhost:7687 standalone          online        online  <NA>    TRUE
#> 2 system localhost:7687 standalone          online        online  <NA>   FALSE
Metadata

Version

0.1.2

License

Unknown

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