List/Fetch pattern and Remote Process Group in Apache NiFi

I do see a lot of questions about how is working the List[X]/Fetch[X] processors and how to load balance the data over the nodes of a NiFi cluster once the data is already in the cluster. Since the question comes up quite often, let’s discuss the subject and let’s try to understand how things are working here.

I will assume that you are running a NiFi cluster since there is no problem about data balancing with a standalone instance 😉

The first thing to understand is: when running a cluster, one of the node is randomly designated as the “Primary node”. The election takes place when the cluster starts, and there is no way to decide which node will be the primary node. OK… you could force things when your cluster starts but there is no point to do such a thing if you want real high availability. So short line is: all nodes may have to be the Primary node at one point and don’t assume that the Primary node will be a given node in particular.

Second thing to understand is: the flow that you are designing on your canvas is running on all the nodes independently. Each node of the cluster is responsible of its own data and a relationship between two processors does not mean that the data going into this relationship will be balanced over the nodes. Unless you use a Remote Process Group (see below) the data will remain on the same node from the beginning to the end of the flow.

I will use a the following example to illustrate my explanations: I want to get files from a remote SFTP server and put the files into HDFS.

  • First idea (bad idea!) / GetSFTP -> PutHDFS

Screen Shot 2017-02-23 at 11.04.42 AM.png

The first option could be the pattern Get/Put which is perfectly fine with a standalone instance. However this will cause issues if you have a NiFi cluster. Remember? The flow is running on all hosts of your cluster. Problem is that you will have concurrent accesses from your nodes to the same files on the SFTP server… and if the processor is configured to delete the file once retrieved (default behavior) you will have errors showing up. Conclusion: always have in mind that a processor is running on all the nodes and can cause concurrent access errors depending on the remote system.

  • Second idea (not efficient!) / GetSFTP on Primary Node -> PutHDFS

The second option is to configure the GetSFTP processor to only run on the Primary Node (in the Scheduling tab of the processor configuration):

Screen Shot 2017-02-23 at 11.10.12 AM.png

This way, you will solve the concurrent accesses since only one node of your cluster (the Primary node) will run the GetSFTP processor.

Brief aside: remember, the flow is running on all the nodes, however if the processor is configured to run on the primary node only, the processor won’t be scheduled on nodes not being the primary node. That’s all.

With this approach the problem is that it’s not efficient at all. First reason is that you get data from only one node (this does not scale at all), and, in the end, only the primary node of your cluster is actually handling the data. Why? Because, unless you explicitly use a remote process group, the data will remain on the same node from the beginning to the end. In this case, only the primary node will actually get data from SFTP server and push it into HDFS.

  • Recommended pattern : ListSFTP -> RPG / Input Port -> FetchSFTP -> PutHDFS

To solve the issues, the List/Fetch pattern has been developed and widely used for a lot of processors. The idea is the following: the List processor will only list the data to retrieve on the remote system and get the associated metadata (it will not get the data itself). For each listed item, a flow file (with no content) will be generated and attributes will be populated with the metadata. Then the flow file is sent to the Fetch processor to actually retrieved the data from the remote system based on the metadata (it can be the path of the file on the remote system for example). Since each flow file contains the metadata of a specific item on the remote system, you won’t have concurrent accesses even if you have multiple Fetch processors running in parallel.

Obviously the List processor is meant to be run on the Primary node only. Then you have to balance the generated flow files over the nodes so that the Fetch processor on each node is dealing with flow files. For this purpose you have to use a Remote Process Group.

A Remote Process Group is an abstract object used to connect two NiFi setup together (the communication between the two NiFi is what we call Site-to-Site or S2S). It can be a MiNiFi instance to a NiFi cluster, a NiFi cluster to another NiFi cluster, a NiFi standalone to a NiFi cluster, etc. And it can also be used to connect a NiFi cluster to itself! This way the flow files will be balanced over all the nodes of the cluster. Few things to know with a Remote Process Group:

  1. You need to have an input port on the remote instance you are connecting to (in our case, you need a remote input port on your canvas).
  2. The address you give when configuring your remote process group does not matter in terms of high availability: once the connection is established with one of the nodes of the remote instance, the remote process group will be aware of all the nodes of the remote instance and will manage the case where the node specified in the address goes down.
  3. Your instances need to be configured to allow remote access. The required properties are:

# Site to Site properties

In the case of our SFTP example, it looks like:

Screen Shot 2017-02-23 at 11.47.40 AM.png

Let’s try to understand what is going on from a cluster perspective. Here is what we have in the case of a 3-nodes NiFi cluster with ListSFTP running on the primary node only:

Screen Shot 2017-02-23 at 12.03.22 PM.png

The ListSFTP when scheduled is going to list the three files on my remote SFTP server and will generate one flow file for each remote file. Each flow file won’t have any content but will have attributes with metadata of the remote files. In the case of ListSFTP, I’ll have (check the documentation at the “Write attributes” paragraph):

Name Description The hostname of the SFTP Server
sftp.remote.port The port that was connected to on the SFTP Server
sftp.listing.user The username of the user that performed the SFTP Listing
file.owner The numeric owner id of the source file The numeric group id of the source file
file.permissions The read/write/execute permissions of the source file
file.lastModifiedTime The timestamp of when the file in the filesystem waslast modified as ‘yyyy-MM-dd’T’HH:mm:ssZ’
filename The name of the file on the SFTP Server
path The fully qualified name of the directory on the SFTP Server from which the file was pulled

The ListSFTP processor will generate 3 flow files and, for now, all flow files are only on the primary node:

Screen Shot 2017-02-23 at 1.59.43 PM.png

Now the Remote Process Group has been configured to connect to the cluster itself, and I set the relationship going from ListSFTP to the Remote Process Group to connect with the input port I created (you may have multiple input ports in the remote system to connect with and you can choose the input port to connect to, that’s up to your needs). When the RPG (Remote Process Group) has the communication enabled, the RPG is aware of the three nodes and will balance the data to each remote node (be aware that there is a lot of parameters for Site-to-Site to improve efficiency). In my case that would give something like:

Screen Shot 2017-02-23 at 1.59.55 PM.png

Note: that would be an ideal case in terms of balancing but, for efficiency purpose, the Site-to-Site mechanism might send batch of flow files to the remote node. In the above example, with only 3 flow files, I would probably not end up with one flow file per node.

Now, since we have everything in the attributes of our flow files, we need to use the Expression Language to set the properties of the FetchSFTP processor to use the attributes of the incoming flow files:


This way, each instance of the FetchSFTP processor will take care of its own file (to actually fetch the content of the remote data) and there won’t be any concurrent access:

Screen Shot 2017-02-23 at 2.00.12 PM.png

All your nodes are retrieving data and you really can scale up your cluster depending on your requirements. Note also that the PutHDFS won’t be an issue neither since each node will write its own file.

As I said previously a lot of processors are embracing this pattern (and this is recommended way to use such processors with a NiFi cluster), and I’d strongly encourage you to do the same when developing your custom processors.

As always questions/comments are welcome.

Debugging Hadoop WebHDFS API

Last week, I found myself unable to use the WebHDFS REST API through an ETL tool. The only error message I got was:

HTTP 400 Bad Request

By looking at the following documentation, I understood that there was only two options:

  • IllegalArgumentException
  • UnsupportedOperationException

Not really helping so I decided to make the API calls myself with curl requests… and here it was with a simple query to list files at the root folder of HDFS as user “123”:

$ curl -i -X PUT -T test.txt "http://mynode:50075/webhdfs/v1/?op=LISTSTATUS&"
HTTP/1.1 400 Bad Request
Content-Type: application/json; charset=utf-8
Content-Length: 209
Connection: close

{"RemoteException":{"exception":"IllegalArgumentException","javaClassName":"java.lang.IllegalArgumentException","message":"Invalid value: \"123\" does not belong to the domain ^[A-Za-z_][A-Za-z0-9._-]*[$]?$"}}

Conclusion is: the user name used with the query is checked against a regular expression and, if not validated, the above exception is returned. The default regular expression being:


I was unable to use WebHDFS because my username was starting by numbers… I understand that this is kind of an edge case: it is rare to have such format in user names but still… I couldn’t believe to be blocked because of this.

After a quick search, I found HDFS-4983 that exposed a property in the HDFS configuration file (from Apache Hadoop 2.3.0) to change the default regular expression. Great! I changed the property (dfs.webhdfs.user.provider.user.pattern), restarted my HDFS service and tested my curl request. The request was successful so I restarted my ETL workflow… and… got the same error! Kind of unexpected…

Back to the basics: making curl requests… My ETL workflow was just trying to load a file into HDFS… So let’s do that manually:

$ curl -i -X PUT "http://mynode:50070/webhdfs/v1/tmp/test.txt?op=CREATE&"
Cache-Control: no-cache
Expires: Sat, 04 Feb 2017 10:19:38 GMT
Date: Sat, 04 Feb 2017 10:19:38 GMT
Pragma: no-cache
Expires: Sat, 04 Feb 2017 10:19:38 GMT
Date: Sat, 04 Feb 2017 10:19:38 GMT
Pragma: no-cache
Set-Cookie: hadoop.auth="u=123&p=123&t=simple&e=1486239578624&s=UrzCjP0SPpPKDJnSYB5BsKuQVKc="; Path=/; HttpOnly
Location: http://mynode:50075/webhdfs/v1/tmp/test.txt?op=CREATE&
Content-Type: application/octet-stream
Content-Length: 0

$ curl -i -X PUT -T test.txt "http://mynode:50075/webhdfs/v1/tmp/test.txt?op=CREATE&"
HTTP/1.1 400 Bad Request
Content-Type: application/json; charset=utf-8
Content-Length: 209
Connection: close

{"RemoteException":{"exception":"IllegalArgumentException","javaClassName":"java.lang.IllegalArgumentException","message":"Invalid value: \"123\" does not belong to the domain ^[A-Za-z_][A-Za-z0-9._-]*[$]?$"}}

As explained here, the first step is to make a request against the Name Node to get the address of a Data Node where the file data is to be written. Then make the second request directly to the Data Node to actually send the data (in this case it’s my test.txt file). And… here is the error again!

So it seems that HDFS-4983 is only fixing read access against the Name Node web interface but not when calling the web interface running with a Data Node… I checked out the code (be careful to check out the code corresponding to the exact version you are running otherwise attaching a debugger won’t be helpful, in my case I got the sources from Hortonworks repositories), and imported it in my Eclipse IDE. A quick search in the code to find occurrences of the regular expression lead me to UserParam class where I found a static import:

import static org.apache.hadoop.hdfs.DFSConfigKeys.DFS_WEBHDFS_USER_PATTERN_DEFAULT;


private static Domain domain = new Domain(NAME, Pattern.compile(DFS_WEBHDFS_USER_PATTERN_DEFAULT));

Meaning that if this domain attribute is not overridden somewhere by a call, then the default regular expression will be used.  It really looks like what we are experiencing!

Just to confirm my assumption, I modified the bootstrap of the Data Node JVM to attach a debugger by adding the following parameters when the JVM is launched:


This way, in Eclipse, I can launch a remote debugger pointing to my Data Node on the port 9999 (ensure this port is opened and available) and define all the breakpoints I want. In this case I set a break point in the channelRead0 method of the WebHdfsHandler class (which is the entry point of the HTTP listener running in the Data Node). This way I confirmed that when checking Users Group Information:

ugi = ugiProvider.ugi();

The user name is checked using the default regular expression. By looking at the patch in HDFS-4983, it was easy to figure out what needed to be added in the code to have the property correctly set in the Data Node web handler. And that’s how I created HDFS-11391 and the associated pull request.

One line of code to fix this issue. Sometimes it’s not that easy. Anyway, it gave me the opportunity to contribute to the Apache Hadoop project… Sweet.

HAProxy load balancing in front of Apache NiFi

There is a lot of situations where load balancing is necessary even more so when you are in a clustered architecture. In the context of NiFi you may want to consider two situations:

  • You have a NiFi cluster and you don’t want to give users the IP address of your NiFi nodes to access the UI (remember: every node of the cluster can be used for the UI or to make REST API calls) and besides you want to load balance users on every node of the cluster. In addition, in case you scale up/down your cluster, you don’t want to inform all the users of such a change.
  • You have Listen[X] processors (HTTP, TCP, UDP, Syslog, etc) in your workflow that are not running on the primary node only and you want to have all the nodes receiving the data (to increase performances and have full scalability). Again you don’t want to configure/inform the data senders with all the IPs of your NiFi nodes, and in case of a cluster change you don’t want to make some changes on client side.

In such situations you need a load balancer that will stand in front of your NiFi cluster and will provide a VIP (Virtual IP). For this purpose, you have hardware options, software options and also cloud options. Keep in mind that, if you want a production setup, you’ll need to have your load balancer installed in a high availability fashion otherwise it’ll become a single point of failure.

In this article, I’ll use HAProxy which is the most widely used open source software based load balancing solution. And I’ll launch my HAProxy instance in a Docker container (I’ll also use Portainer as a UI helping me to manage my Docker environment).

Some useful links that can help you with the different tools I’m going to use:

I assume I already have my secured NiFi 3-nodes cluster up and running. And also, I’ve already setup my Docker and Portainer environment: I’m ready to pull HAProxy Docker image and to create my container.

Let’s start with my HAProxy instance. First of all, in Portainer, I just need to pull the image I want (in this case I want the latest version and I just need to enter haproxy):

Screen Shot 2017-02-08 at 12.23.09 PM.png

I now have the image available:


Let’s build a container. In order to ease the modification of the configuration file of HAProxy, I’ll define a bind mount to bind the configuration file inside the container to a file I have on my computer. I also need to define all the ports I want to expose in my container. Since my container will run on one of the nodes of my cluster I don’t want to use the same ports (but in practice, your HAProxy would probably be on its own host).

  • Open my container on 9443, and I’ll configure HAProxy to listen on 9443 and to redirect requests made on 9443 to my NiFi nodes on port 8443 (port of my NiFi UI)
  • Open my container on 9999, and I’ll configure HAProxy to listen on 9999 and to redirect requests made on 9999 to my NiFi nodes on port 8888 (port that I’ll use for my ListenHTTP processors)
  • Open my container on 1936 and map on port 1936 inside my container (that’s the port used by the HAProxy management UI)

In Portainer, I add a container and define the following:

Screen Shot 2017-02-08 at 2.42.02 PM.png

When I create my container, it will immediately stop because I didn’t configure my configuration file so far and the container won’t start if the configuration file is invalid or does not exist. You can check the logs of your container in Portainer in case of issue.

In our case we’ll have HTTP access to send data to our ListenHTTP processors and HTTPS to access the UI. In case of HTTPS, I don’t want to have my load balancer taking care of certificates and I just want to have my requests going through (pure TCP load balancing)… this will raise an issue to users accessing the UI because the certificate presented by the NiFi node won’t match the address the client is requesting (load balancer address), this could be solved by adding a SAN (Subject Alternative Name) in the certificate of the nodes but this will be discussed in another article (in the mean time you can have a look at NIFI-3331). In this case (and just because this is a demo!), I’ll accept the SSL exceptions in my browser.

OK so let’s see my HAProxy configuration file:


    log     global
    mode    http
    option  httplog
    option  dontlognull
    timeout connect 5000
    timeout client  50000
    timeout server  50000

frontend nifi-ui
    bind *:9443
    mode tcp
    default_backend nodes-ui

backend nodes-ui
    mode tcp
    balance roundrobin
    stick-table type ip size 200k expire 30m
    stick on src
    option httpchk HEAD / HTTP/1.1\r\nHost:localhost
    server nifi01 node-1:8443 check check-ssl verify none
    server nifi02 node-2:8443 check check-ssl verify none
    server nifi03 node-3:8443 check check-ssl verify none

frontend nifi-listen-http
    bind *:9999
    mode http
    default_backend nodes-http

backend nodes-http
    mode http
    balance roundrobin
    option forwardfor
    http-request set-header X-Forwarded-Port %[dst_port]
    option httpchk HEAD / HTTP/1.1\r\nHost:localhost
    server nifi01 node-1:8888 check
    server nifi02 node-2:8888 check
    server nifi03 node-3:8888 check

listen stats
    bind *:1936
    mode http
    stats enable
    stats uri /
    stats hide-version
    stats auth admin:password

Let’s see the different parts:

  • global – I put nothing in here
  • defaults – Just some timeouts and log configuration, nothing special
  • frontend nifi-ui – here I define a front end called “nifi-ui”. This is where I define on what port HAProxy should listen (in this case on port 9443, for TCP mode) and where I should redirect the requests (in this case to my back end called nodes-ui).
  • backend nodes-ui – here I define my back end where will be redirected my requests received by my front end. I define TCP mode, round robin load balancing, stickiness (to ensure that a connected user, based on its IP, will remain on the same node over multiple requests), and the nodes available. I also define the health check operation performed by HAProxy to confirm if nodes are up or down. In this case it’s a HEAD HTTP request and I don’t check the SSL certificates.
  • frontend nifi-listen-http – here I define the front end that will be used to send data to my ListenHTTP processors on port 9999.
  • backend nodes-ui – here I define the back end with my servers, the HTTP mode, the health check, and also the addition of two HTTP headers (x-forwarded-port and x-forwarded-for) to keep track of IP and port of my client (otherwise I’d only know about the IP and port of my load balancer when receiving data in NiFi).
  • listen stats – here are some parameters about the HAProxy management UI, like the port, the login and password, etc.

I restart my container to take into account the configuration, and I can have a look to the management UI:


All is green meaning that our health checks are OK.

Assuming my load balancer has the following host name “my-nifi-vip”, I can now access the UI through https://my-nifi-vip:9443/nifi :


On my UI, I can configure a ListenHTTP processor as below:

Screen Shot 2017-02-08 at 4.43.14 PM.png


And send data to my cluster using the virtual IP provided by my load balancer:

while true; do curl -X POST http://my-nifi-vip:9999/test; done;

In the HAProxy management UI, I can confirm that my requests are correctly load balanced on all the nodes of my cluster:


It is now really easy to add or remove new nodes in your NiFi cluster without impacting the clients sending data into NiFi since they only need to know about the virtual IP exposed by the load balancer. You just need to update the configuration file when you are adding nodes, and restart your HAProxy container.

Keep in mind that even if the data is correctly load balanced over the nodes, all the requests are going through a single point, the load balancer. Consequently, on a performance standpoint, your load balancer may become a bottleneck in case you need to handle a very large number of connections per second. However load balancers are designed to be as efficient as possible and you should be OK in most cases.

As always questions/comments are welcomed.

Using counters in Apache NiFi

You may not know it but you have the availability to define and play with counters in NiFi. If policies are correctly configured (if your NiFi is secured), you should be able to access the existing counters using the menu:

Screen Shot 2017-02-07 at 5.33.59 PM.png

Counters are just values that you can increase or decrease of a given delta. This is useful if you want to monitor particular values along your workflow. At the moment, unless you use a processor that explicitly uses counters or provides a way to define counters, there is nothing available out of the box.

The best way to define and update counters is to use ExecuteScript processor with the following piece of Groovy code:

def flowFile = session.get()
if(!flowFile) return
session.adjustCounter("my-counter", 1, true)
session.transfer(flowFile, REL_SUCCESS)

With this example, the ExecuteScript processor will just transmit the flow file without any modification to the success relationship but will also increment the counter “my-counter” of 1. If this counter does not exist it will be initialized with the delta value given as argument.

Here is the documentation of this method:

     * Adjusts counter data for the given counter name and takes care of
     * registering the counter if not already present. The adjustment occurs
     * only if and when the ProcessSession is committed.
     * @param name the name of the counter
     * @param delta the delta by which to modify the counter (+ or -)
     * @param immediate if true, the counter will be updated immediately,
     *            without regard to whether the ProcessSession is commit or rolled back;
     *            otherwise, the counter will be incremented only if and when the
     *            ProcessSession is committed.
    void adjustCounter(String name, long delta, boolean immediate);

Let’s see an example: I want to confirm the correct behavior of the GetHDFS processor when I have multiple instances of this processor looking into the same directory but getting different flow files based on a regular expression.

Here is the first part of my flow:


Basically, I am generating flow files every 1ms with GenerateFlowFile. The generated flow files will be named after the generation date timestamp (without any extension). I am sending the files into HDFS and then I’m using a RouteOnAttribute where I check the filename according to a regular expression to split files according to even and uneven names. This way I can increment counters tracking the number of files I sent to HDFS with even names and with uneven names.

Here is the second part of my flow:

Screen Shot 2017-02-07 at 6.27.28 PM.png

I have two instances of GetHDFS processor configured to look into the same input directory but one with a regular expression to look for files with an even name, and one to look for files with an uneven name, this way there is no concurrent access. Besides, the processor is configured to delete the file on HDFS once the file is retrieved in NiFi. Then I update two different counters to track the number of files with an even name that I retrieved from HDFS, and one for files with an uneven name.

If everything is working correctly, I should be able to let run my workflow a bit, then stop the generation of flow files, wait for all the flow files to be processed and confirm that:

  • even-producer counter is equal to even-consumer counter
  • unenven-producer counter is equal to uneven-consumer counter

Let’s have a look into our counters table:


It looks like we are all good 😉

As a remark, if you have multiple processors updating the same counter, then you will have the global value of the counter but also the value at each processor level. For example, if I have:


With both ExecuteScript incrementing the same “test” counter, then, I’ll have:


Also, as a last remark, you can notice that it’s possible to reset a counter to 0 from the counters table with the button in the last column (assuming you have write access to the counters based on the defined policies). It can be useful when doing some tests.

As always, questions/comments are welcomed!

NiFi and OAuth 2.0 to request WordPress API

A lot of famous websites are allowing you to develop custom applications to interact with their API. In a previous example, we saw how to use NiFi to perform OAuth 1.0A authentication against Flickr API. However a lot of websites are using OAuth 2.0 mechanism to authenticate your applications. You can find more details here, and check the differences between the two versions here.

Since this blog is hosted and powered by WordPress, and since WordPress is allowing you to develop applications and is using Oauth 2.0 as authentication mechanism, let’s try to get the statistics of my blog using NiFi.

Before going into the details, let’s recap the behavior in play with the example of WordPress: a user A develops an application X, this application X is running on the Internet. Then a user B is accessing to the application X. This application X is asking B to grant a set of permissions to access AS user B to WordPress. If user B accepts, then application X can interact with WordPress as user B.

This is something you must have experienced with some applications like Facebook, Google, Instagram, LinkedIn, etc… All asking your permissions to post some content in your name on other websites/applications.

Now let’s understand what is going on from an OAuth 2.0 point of view.

When user B accesses application X, the application X is issuing a request to WordPress saying that the application X is requesting access to WordPress resources. The user B will be asked to authenticate with its WordPress credentials and to approve the request of the application X to grant the application a set of permissions on the resources belonging to B. Once done, the application X will get from WordPress a short time limited code. Then, the application is going to issue another request to WordPress using this code and telling which resource the application wants to access. WordPress will then return an access token and the ressource ID the application is allowed to use in API calls. At this point, the application is able to request all the API endpoints to get all the data of the given resource (a WordPress blog in this example).

OK… So now, let’s build our application using NiFi!

I’ll demonstrate something “simple”: a web service exposed by NiFi that gives users access to the stats of their blog. (in the example, it will be my blog since I’ll be connecting to my application using my credentials, but that could be any WordPress user)

Let’s define my application in WordPress so that WordPress is aware of this application and generates me some secret tokens to identify my application. I go here and I create an application that I call NiFi. Notice that the redirect URL is http://localhost:9999/ because this is where the web service created in NiFi will be listening. This could be something online but my NiFi would need to be opened on the Internet.


The redirect URL will be the endpoint where the user will be redirected once the user has granted access to the application to WordPress resources belonging to the user. In this case we want to send back the user to our listening web service. It might be easier to understand later with the example, don’t worry 😉

Once my application is created, WordPress gives me some information that will be particularly useful:


That’s all we need on WordPress side. Let’s start building our NiFi workflow!

In the end the workflow will be:

Screen Shot 2017-02-01 at 12.24.29 AM.png

We start with a HandleHttpRequest that is listening to requests performed by the user. We specify the processor to listen on localhost:9999.

Then I use an UpdateAttribute processor to add all the “common properties” I want to access in all my processors through expression language:

Screen Shot 2017-02-01 at 12.13.51 AM.png

Then I use a RouteOnAttribute to route the request based on the URL. Indeed, I am expecting users to access my web service with the URL http://localhost:9999/getCode but WordPress will also send requests to my service when redirecting users on URL like http://localhost:9999/code=…&state.

Here is my RouteOnAttribute:

Screen Shot 2017-02-01 at 12.16.07 AM.png

When this is a request sent by a user (containing “getCode” in the URL), then I use a InvokeHTTP processor to send a request to WordPress. This will give me the page where I need to send my user so that the user can authenticate and grant my application all permissions.

Based on WordPress documentation, the URL to request with a GET is:


And what I received from WordPress (basically the page to let the user authenticate himself) is what I return to the user through a HandleHttpResponse processor. This way the user will access the page to authenticate on WordPress and grant my application all permissions, then the user will be redirected back to my application with a URL containing the code I need to get a token (thanks to the redirect URL we defined).

When the redirection is performed, I am back to my HandleHttpRequest, but, this time, at the RouteOnAttribute, I’ll go in unmatched relationship (no “getCode” in the URL since, this time, this is the redirect URL). At this point, I use an UpdateAttribute to extract the code from the callback URL used by WordPress:


I am now able to create the content that will be sent to WordPress in the next request using a ReplaceText processor (indeed, since it will be a POST request, I need to update the content of my FlowFile because this will be used as the body of my next HTTP request):

Screen Shot 2017-02-01 at 12.25.38 AM.png

And I can perform my POST request using a InvokeHTTP processor in which I specify the content type to “application/x-www-form-urlencoded”.

This request will give me back a JSON looking like:

Screen Shot 2017-02-01 at 12.27.00 AM.png

So I use an EvaluateJsonPath processor to extract the blog ID and the access token:

Screen Shot 2017-02-01 at 12.27.53 AM.png

And I am now able to perform my last request with a InvokeHttp to request the API endpoint of WordPress to get statistics associated to the blog ID:

Screen Shot 2017-02-01 at 12.28.58 AM.png

And I add a property to specify my access token as a header property:

Screen Shot 2017-02-01 at 12.29.33 AM.png

Then I send back the result to a HandleHttpResponse to display the result of the request to the user. Obviously at this point we could do something nicer with the statistics and display some charts for example… but that’s outside the purpose of this blog: I just return the JSON containing the statistics 🙂

That’s all! Let’s now see what it looks like when connecting to the web service while the full flow is running:

When I go to http://localhost:9999/getCode

I get to this page:

Screen Shot 2017-02-01 at 12.32.23 AM.png

I enter my credentials, and since I’ve a two-steps authentication, I get on a web page asking for another access code that I received on my smartphone. Once the code is entered, I am asking to grant permissions to the application:

Screen Shot 2017-02-01 at 12.35.44 AM.png

Then I approve, and I finally get the statistics in a JSON:

Screen Shot 2017-02-01 at 12.36.55 AM.png

That’s pretty cool, isn’t it? The template is available here.

Now I’m sure you can imagine a lot of great applications using OAuth 2.0 mechanism to interact with various existing APIs!

As always, comments and questions are welcomed! I hope you enjoyed this blog!

Integration of NiFi with LDAP

Once your cluster is secured, you probably want to start allowing users to access the cluster and you may not want to issue individual certificates for each user. In this case, one of the option is to use LDAP as the authentication provider of NiFi. This is quite simple, and we’ll see in this post how to easily setup a local LDAP server and integrate NiFi with it.

In terms of configuration, everything is done with two files:

  • ./conf/
  • ./conf/login-identity-providers.xml

In, we are interested by two properties:


The first one is used to give the path to the login-identity-providers.xml and the second one is used to define the name of the identity provider to use from the XML file (in case you configured multiple providers).

A quick quote from the documentation:

NiFi supports user authentication via client certificates or via username/password. Username/password authentication is performed by a Login Identity Provider. The Login Identity Provider is a pluggable mechanism for authenticating users via their username/password. Which Login Identity Provider to use is configured in two properties in the file.

The nifi.login.identity.provider.configuration.file property specifies the configuration file for Login Identity Providers. The property indicates which of the configured Login Identity Provider should be used. If this property is not configured, NiFi will not support username/password authentication and will require client certificates for authenticating users over HTTPS. By default, this property is not configured meaning that username/password must be explicitly enabled.

NiFi does not perform user authentication over HTTP. Using HTTP all users will be granted all roles.

In other words, if you want login/password authentication, your cluster needs to be secured first!

OK, so I set the following values in


And then I just need to configure my XML files and to restart NiFi. Here are the LDAP parameters (and we can notice that the identifier is matching the value set in

        <property name="Authentication Strategy">START_TLS</property>
        <property name="Manager DN"></property>
        <property name="Manager Password"></property>
        <property name="TLS - Keystore"></property>
        <property name="TLS - Keystore Password"></property>
        <property name="TLS - Keystore Type"></property>
        <property name="TLS - Truststore"></property>
        <property name="TLS - Truststore Password"></property>
        <property name="TLS - Truststore Type"></property>
        <property name="TLS - Client Auth"></property>
        <property name="TLS - Protocol"></property>
        <property name="TLS - Shutdown Gracefully"></property>
        <property name="Referral Strategy">FOLLOW</property>
        <property name="Connect Timeout">10 secs</property>
        <property name="Read Timeout">10 secs</property>
        <property name="Url"></property>
        <property name="User Search Base"></property>
        <property name="User Search Filter"></property>
        <property name="Identity Strategy">USE_DN</property>
        <property name="Authentication Expiration">12 hours</property>

And here is the associated documentation:

Identity Provider for users logging in with username/password against an LDAP server.

‘Authentication Strategy’ – How the connection to the LDAP server is authenticated. Possible values are ANONYMOUS, SIMPLE, LDAPS, or START_TLS.

‘Manager DN’ – The DN of the manager that is used to bind to the LDAP server to search for users.
‘Manager Password’ – The password of the manager that is used to bind to the LDAP server to search for users.

‘TLS – Keystore’ – Path to the Keystore that is used when connecting to LDAP using LDAPS or START_TLS.
‘TLS – Keystore Password’ – Password for the Keystore that is used when connecting to LDAP using LDAPS or START_TLS.
‘TLS – Keystore Type’ – Type of the Keystore that is used when connecting to LDAP using LDAPS or START_TLS (i.e. JKS or PKCS12).
‘TLS – Truststore’ – Path to the Truststore that is used when connecting to LDAP using LDAPS or START_TLS.
‘TLS – Truststore Password’ – Password for the Truststore that is used when connecting to LDAP using LDAPS or START_TLS.
‘TLS – Truststore Type’ – Type of the Truststore that is used when connecting to LDAP using LDAPS or START_TLS (i.e. JKS or PKCS12).
‘TLS – Client Auth’ – Client authentication policy when connecting to LDAP using LDAPS or START_TLS. Possible values are REQUIRED, WANT, NONE.
‘TLS – Protocol’ – Protocol to use when connecting to LDAP using LDAPS or START_TLS. (i.e. TLS, TLSv1.1, TLSv1.2, etc).
‘TLS – Shutdown Gracefully’ – Specifies whether the TLS should be shut down gracefully before the target context is closed. Defaults to false.

‘Referral Strategy’ – Strategy for handling referrals. Possible values are FOLLOW, IGNORE, THROW.
‘Connect Timeout’ – Duration of connect timeout. (i.e. 10 secs).
‘Read Timeout’ – Duration of read timeout. (i.e. 10 secs).

‘Url’ – Url of the LDAP server (i.e. ldap://<hostname>:<port>).
User Search Base’ – Base DN for searching for users (i.e. CN=Users,DC=example,DC=com).
User Search Filter’ – Filter for searching for users against the ‘User Search Base’. (i.e. sAMAccountName={0}). The user specified name is inserted into ‘{0}’.

‘Identity Strategy’ – Strategy to identify users. Possible values are USE_DN and USE_USERNAME. The default functionality if this property is missing is USE_DN in order to retain backward compatibility. USE_DN will use the full DN of the user entry if possible. USE_USERNAME will use the username the user logged in with.
‘Authentication Expiration’ – The duration of how long the user authentication is valid for. If the user never logs out, they will be required to log back in following this duration.

OK, enough theory, let’s install a LDAP server using Apache Directory Studio. This project provides an easy way to setup a LDAP server but is also providing a great GUI to manage/administrate existing LDAP servers.I’ll go quick because it’s quite simple to setup and if needed the documentation of the official website is very useful.

Once downloaded and installed, just launch it. On the workbench, we are going to create a new server. Click on the ‘+’ symbol in the “LDAP Servers” tab:


Then, select Apache DS and give it a name:

Screen Shot 2017-01-24 at 10.04.16 PM.png

Create a connection: right click on your server / create a connection. And start your server to access it. You should be able to access the Overview tab of your server. We are going to create a partition/branch for NiFi users:

Screen Shot 2017-01-24 at 10.04.52 PM.png

Click on Advanced Partitions configuration and then Add a new partition. Here I decided to call my partition “dc=nifi,dc=com”:

Screen Shot 2017-01-24 at 10.05.14 PM.png

At this point, you need to restart your server (right click / stop, right click / start).

Now we are going to create an organizational unit for groups and an organizational unit for people. In the ou=groups, we will define two groups, one for normal users and one for administrators. And we are going to create one user in each group, a user “test” in the group “users”, and a user “admin” in the group “admins”. This can be done through the GUI but in this case, I’ll do it by importing the below LDIF file:

dn: ou=people,dc=nifi,dc=com
objectclass: organizationalUnit
objectClass: extensibleObject
objectclass: top
ou: people

dn: ou=groups,dc=nifi,dc=com
objectclass: organizationalUnit
objectClass: extensibleObject
objectclass: top
ou: groups

dn: cn=users,ou=groups,dc=nifi,dc=com
objectClass: groupOfUniqueNames
objectClass: top
cn: users
uniqueMember: cn=test,ou=people,dc=nifi,dc=com

dn: cn=admins,ou=groups,dc=nifi,dc=com
objectClass: groupOfUniqueNames
objectClass: top
cn: admins
uniqueMember: cn=admin,ou=people,dc=nifi,dc=com

dn: cn=test,ou=people,dc=nifi,dc=com
objectclass: inetOrgPerson
objectclass: organizationalPerson
objectclass: person
objectclass: top
cn: test
description: A test user
sn: test
uid: test
userpassword: password

dn: cn=admin,ou=people,dc=nifi,dc=com
objectclass: inetOrgPerson
objectclass: organizationalPerson
objectclass: person
objectclass: top
cn: admin
description: A admin user
sn: admin
uid: admin
userpassword: password

To import it, right click on dc=nifi,dc=com, then Import, then LDIF import and select your file.

This will give you the following structure:

Screen Shot 2017-01-24 at 10.27.40 PM.png

Now we want to configure NiFi to connect to our LDAP server. For that you have to note that, by default, the manager of the server (for an Apache DS LDAP server) has “uid=admin,ou=system” as DN and “secret” as password. Then the XML file is configured as below (no LDAPS/TLS in this example):

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
        <property name="Authentication Strategy">SIMPLE</property>

        <property name="Manager DN">uid=admin,ou=system</property>
        <property name="Manager Password">secret</property>

        <property name="Referral Strategy">FOLLOW</property>
        <property name="Connect Timeout">10 secs</property>
        <property name="Read Timeout">10 secs</property>

        <property name="Url">ldap://localhost:10389</property>
        <property name="User Search Base">ou=people,dc=nifi,dc=com</property>
        <property name="User Search Filter">uid={0}</property>

        <property name="Identity Strategy">USE_USERNAME</property>
        <property name="Authentication Expiration">12 hours</property>

We need to restart NiFi to take into account the modifications. Note: if NiFi is clustered, configuration files must be the same on all nodes.

Now… if you try to connect as test or admin, you will get the following error:

Unknown user with identity ‘admin’. Contact the system administrator.

This is because you first need to add this user in the list of users through NiFi UI using the initial admin account (see Apache NiFi 1.1.0 – Secured cluster setup). At there is no syncing mechanism to automatically add LDAP users/groups into NiFi.

When connected with your initial admin account (using your individual certificate), go into users to add your users, and then into policies to grant access and rights to the users:

Screen Shot 2017-01-24 at 10.45.35 PM.png

Screen Shot 2017-01-24 at 10.45.46 PM.png

You have now a NiFi instance integrated with a LDAP server and you can connect as different users defined in your LDAP. It gives you the opportunity to add users and play with the policy model implemented in NiFi.

Important note: NiFi has a large and active community, new features regarding LDAP integration could be provided very soon (for example: NIFI-3115).

As always, comments/remarks are welcomed!

Scaling up/down a NiFi cluster

Scaling up – add a new node in the cluster

You have a NiFi cluster and you are willing to increase the throughput by adding a new node? Here is a way to do it without restarting the cluster. This post starts with a 3-nodes secured cluster with embedded ZooKeeper and we are going to add a new node to this cluster (and this new node won’t have an embedded ZK).

The node I’m going to add is a CentOS 7 virtual machine running an Apache NiFi 1.1.0 instance. All prerequisites are met (network, firewall, java, etc) and I uncompressed the NiFi and NiFi toolkit binaries archives.

First thing to do is, if you don’t have DNS resolution, to update the /etc/hosts file on all the nodes so that each node can resolve the others.

Then, I want to issue a certificate signed by my Certificate Authority for my new node. For this purpose, I use the NiFi toolkit and issue a CSR against my running CA server (see secured cluster setup). I created a directory /etc/nifi, and from this directory I ran the command:

.../bin/ client -c node-3 -t myTokenToUseToPreventMITM -p 9999

node-3 being the node where my CA server is running.

It generates:

  • config.json
  • keystore.jks
  • nifi-cert.pem
  • truststore.jks

Then I can configure my new node with the following properties in ./conf/ (to match the configuration used on the running cluster):

And the following properties based on the information from the generated config.json file:

Then we need to configure the ./conf/authorizers.xml file to specify the initial admin identity and the nodes identities:

        <property name="Authorizations File">./conf/authorizations.xml</property>
        <property name="Users File">./conf/users.xml</property>
        <property name="Initial Admin Identity">CN=pvillard, OU=NIFI</property>
        <property name="Legacy Authorized Users File"></property>

        <property name="Node Identity 1">CN=node-1, OU=NIFI</property>
        <property name="Node Identity 2">CN=node-2, OU=NIFI</property>
        <property name="Node Identity 3">CN=node-3, OU=NIFI</property>

IMPORTANT: the authorizers.xml file must match the file that is on the other nodes. We do not specify the Node Identity of the new node, this will be handled when the node is joining the cluster. Also, before starting your new node, delete the ./conf/flow.xml.gz file so that this new node will pick up the current flow definition from the running cluster.

At this point, you can start the new node:

./bin/ start && tail -f ./logs/nifi-app.log

And you will be able to see in the cluster view in the NiFi UI that your new node has joined the cluster:


You now need to add the new user corresponding to the new node:



And then update the policies to grant proxy “user requests” write access to the new node.


Now I want to confirm that my new node is used in the workflow processing. I am going to create a simple workflow that generates flow files on primary node, distribute the load on all the nodes of the cluster and store the generated files in /tmp. To do that, I first need to grant me the rights to modify the root process group content:

Click on the key symbol on the canvas and grant yourself all the access.


Then in order to simplify the next tasks (grant permissions to nodes for site-to-site communications), I recommend you to create a group called “nodes” and to add all the nodes user inside this group:


Then I create my workflow with a Remote Process Group and an Input Port to ensure the load balancing:


And I also specify that my GenerateFlowFile processor is running on primary node only:


Besides, I add specific rights to the Input Port to allow site-to-site communication between nodes. To do that, select the Input Port, then click on the key symbol in the Operate Panel and grant “receive site-to-site data” to the “nodes” group.

I can now start my workflow and confirm that data is stored in /tmp on each one of my nodes. I now have a new node participating in the execution of the workflow by the NiFi cluster!

Scaling down – decommission a node of the cluster

OK… now we want to check how a node can be decommissioned. There is a lot of reasons to be in this situation but the most common ones are:

  • upgrade the cluster in a rolling fashion (decommission a node, upgrade the node, move back the node in the cluster and move on to the next one)
  • add a new processor NAR to the cluster (decommission a node, add NAR in the node’s library, restart NiFi on this node, move back the node in the cluster and move on to the next one)

To do that, you just need to go in the cluster view, disconnect your node, stop your node, perform your modifications and restart the node to get it back in the cluster. Coordinator and primary roles will be automatically assigned to a new node if needed.

But let’s say we are in more a “destructive” situation (removing a node for good) and we want to ensure that the data currently processed by the node we are decommissioning is correctly processed before shutting down NiFi on this node.For this purpose, I am going to change the end point of my workflow with a PutHDFS instead of a PutFile and send the data to an external cluster. The objective is to check that all the generated data is correctly going into HDFS without any issue.Here is my workflow:screen-shot-2016-11-30-at-9-16-54-amAnd here is the current status of my cluster:screen-shot-2016-11-30-at-9-18-29-amMy GenerateFlowFile is running on the primary node only (node-1) and I’ll generate a file every 100ms. I’ll decommission the node-1 to also demonstrate the change of roles.

As a note: when you define a remote process group, you need to specify one of the nodes of the remote cluster you want to send data to. This specific node is only used when you are starting the remote process group to connect to the remote cluster. Once done, the RPG will be aware of all the nodes of the remote cluster and will be able to send data to all the nodes even though the specified remote node is disconnected. In a short future, it’ll be possible to specify multiple remote nodes in order to be more resilient (in case the RPG is stopped/restarted and the specified remote node is no more available).

To decommission a node, I only need to click on the “disconnect” button on the cluster view for the node I want to disconnect.Before disconnecting my node, I can check that my workflow is running correctly and I have flow files queued in my relationships:screen-shot-2016-11-30-at-9-31-46-amI can now disconnect my node-1 and check what is going on. Roles have been reassigned and the workflow is still running:screen-shot-2016-11-30-at-9-33-43-amscreen-shot-2016-11-30-at-9-33-55-amNote that, as I explained, the remote process group is still working as expected even though it was using node-1 as remote node (see note above).I can now access the UI of the node I just disconnected and check the current status of this node (https://node-1:8443/nifi). When I access the node, I’ve the following warning:screen-shot-2016-11-30-at-9-35-15-amAnd I can see that the workflow is still running on this node. This way, I can wait until all flow files currently on this node are processed:screen-shot-2016-11-30-at-9-35-27-amMy GenerateFlowFile is not running anymore since my node lost its role of Primary Node, and we can wait for the end of the processing of all flow files on this node. Once all flow files are processed, we have the guarantee that there will be no data loss and we can now shutdown the node if needed.If you want to reconnect it once you have performed your updates, you just need to go on the UI (from a node in the cluster), go in the cluster view and reconnect the node:screen-shot-2016-11-30-at-9-33-43-amThe node is now reconnected and used in the workflow processing:screen-shot-2016-11-30-at-9-43-24-amI can check that all the files I’ve generated have been transferred, as expected, on my HDFS cluster.screen-shot-2016-11-30-at-9-45-25-amThat’s all for this blog! As you can see, scaling up and down your NiFi cluster is really easy and it gives you the opportunity to ensure no service interruption.As always, comments and suggestions are welcomed.