Skip to main content

New Features of Apache NiFi 1.13.2

 New Features of Apache NiFi 1.13.2

New Features
  • ListenFTP
  • UpdateHiveTable - Hive DDL changes -Hive Update Schema ie Data Drift ie Hive Schema Migration!!!!
  • SampleRecord - different sampling approaches to records (Interval Sampling, Probabilistic Sampling, Reservoir Sampling)
  • CDC Updates
  • Kudu updates
  • AMQP and MQTT Integration Upgrades
  • ConsumeMQTT - readers and writers added
  • HTTP access to NiFi by default is now configured to accept connections to only.  If you want to allow broader access for some reason for HTTP and you understand the security implications you can still control that as always by changing the '' property in as always. That said, please take the time to configure proper HTTPS.  We offer detailed instructions and tooling to assist.
  • ConsumeMQTT - add record reader/writer
  • The ability to run NiFi with no GUI as MiNiFi/NiFi combined code base continues.
  • Support for Kudu Dates (
  • Updated GRPC versions
  • Apache Calcite update
  • PutDatabaseRecord update

Here is an example NiFi ETL Flow:

Example NiFi 1.13.2 Flow:
  • ConsumeMQTT:   now with readers
  • UpdateAttribute:   set to kafka and to json.
  • SampleRecord:   sample a few of the records
  • PutRecord:   Use reader and destination service
  • UpdateHiveTable:   new sink
Consume from MQTT and read and write to/from records.

Some example attributes from a running flow:

Connection Pools for DatabaseRecordSinks can be JDBC, Hadoop and Hive.

FreeFormTextRecordSetWriter is great for writing any format.

RecordSinkService we will pick Kafka as our destination.

KafkaRecordSink from PutRecord

Reader will pick json in our example based on our UpdateAttribute, we can dynamically change this as data streams.

ReaderLookup  - lets you pick a reader based on an attribute.

We have defined readers for Parquet, JSON, AVRO, XML and CSV so no matter the type I can automagically read it.    Great for reusing code and great for cases like our new ListenFTP where you may get sent tons of different files to process.   Use one FLOW!

RecordSinkService can help you make all our flows generic so you can drop in different sinks/destinations for your writers based on what the data coming in is.   This is revolutionary for code reuse.

We can write our output in a custom format that could look like a document, HTML, fixed width, a form letter, weird delimiter or whatever you need.

Sample records using different methods.

We use the RecordSinkServiceLookup to allow us to change our sink location dynamically, we are passing in an attribute to choose Kafka.

We have pushed our data to Kafka via the KafkaRecordSink.  We can see our data easily in Streams Messaging Manager (SMM).

With a RecordReaderFactory, you can pick readers like the new WindowsEventLogReader.

As another output, we can UpdateHiveTable from our data and change the table as needed.

Straight From Release Notes:  New Feature
  • [NIFI-7386] - AzureStorageCredentialsControllerService should also connect to storage emulator
  • [NIFI-7429] - Add Status History capabilities for system level metrics
  • [NIFI-7549] - Adding Hazelcast based implementation for DistributedMapCacheClient
  • [NIFI-7624] - Build a ListenFTP processor
  • [NIFI-7745] - Add a SampleRecord processor
  • [NIFI-7796] - Add Prometheus metrics for total bytes received and bytes sent for components
  • [NIFI-7801] - Add acknowledgement check to Splunk
  • [NIFI-7821] - Create a Cassandra implementation of DistributedMapCacheClient
  • [NIFI-7879] - Create record path function for UUID v5
  • [NIFI-7906] - Add graph processor with flexibility to query graph database conditioned on flowfile content and attributes
  • [NIFI-7989] - Add Hive "data drift" processor
  • [NIFI-8136] - Allow State Management to be tied to Process Session
  • [NIFI-8142] - Add "on conflict do nothing" feature to PutDatabaseRecord
  • [NIFI-8146] - Allow RecordPath to be used for specifying operation type and data fields when using PutDatabaseRecord
  • [NIFI-8175] - Add a WindowsEventLogReader

An update Cloudera Flow Management!

Cloudera Flow Management on DataHub Public Cloud 

This minor update has some Schema Registry and Atlas integration updates.  

If that wasn't enough, new version of MiNiFi C++ Agent!

Cloudera Edge Manager 1.2.2 Release

February 15, 2021

CEM MiNiFi C++ Agent - 1.21.01 release includes:
  • Support for JSON output in the Consume Windows Even Log processor
  • Full Expression Language support on Windows
  • Full S3 support (List, Fetch, Get, Put)

Remember when you are done.

Popular posts from this blog

Ingesting Drone Data From DJII Ryze Tello Drones Part 1 - Setup and Practice

Ingesting Drone Data From DJII Ryze Tello Drones Part 1 - Setup and Practice In Part 1, we will setup our drone, our communication environment, capture the data and do initial analysis. We will eventually grab live video stream for object detection, real-time flight control and real-time data ingest of photos, videos and sensor readings. We will have Apache NiFi react to live situations facing the drone and have it issue flight commands via UDP. In this initial section, we will control the drone with Python which can be triggered by NiFi. Apache NiFi will ingest log data that is stored as CSV files on a NiFi node connected to the drone's WiFi. This will eventually move to a dedicated embedded device running MiniFi. This is a small personal drone with less than 13 minutes of flight time per battery. This is not a commercial drone, but gives you an idea of the what you can do with drones. Drone Live Communications for Sensor Readings and Drone Control You must connect t

NiFi on Cloudera Data Platform Upgrade - April 2021

CFM 2.1.1 on CDP 7.1.6 There is a new Cloudera release of Apache NiFi now with SAML support. Apache NiFi Apache NiFi Registry See:   For changes: Get your download on: To start researching for the future, take a look at some of the technical preview features around Easy Rules engine and handlers. Make sure you use the latest possible JDK 8 as there are some bugs out there.   Use a recent v

Using Apache NiFi in OpenShift and Anywhere Else to Act as Your Global Integration Gateway

Using Apache NiFi in OpenShift and Anywhere Else to Act as Your Global Integration Gateway What does it look like? Where Can I Run This Magic Engine: Private Cloud, Public Cloud, Hybrid Cloud, VM, Bare Metal, Single Node, Laptop, Raspberry Pi or anywhere you have a 1GB of RAM and some CPU is a good place to run a powerful graphical integration and dataflow engine.   You can also run MiNiFi C++ or Java agents if you want it even smaller. Sounds Too Powerful and Expensive: Apache NiFi is Open Source and can be run freely anywhere. For What Use Cases: Microservices, Images, Deep Learning and Machine Learning Models, Structured Data, Unstructured Data, NLP, Sentiment Analysis, Semistructured Data, Hive, Hadoop, MongoDB, ElasticSearch, SOLR, ETL/ELT, MySQL CDC, MySQL Insert/Update/Delete/Query, Hosting Unlimited REST Services, Interactive with Websockets, Ingesting Any REST API, Natively Converting JSON/XML/CSV/TSV/Logs/Avro/Parquet, Excel, PDF, Word Documents, Syslog, Kafka, JMS, MQTT, TCP