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Lenses 2.1 Release

Stefan Bocutiu
By Stefan BocutiuAugust 9, 2018
hero
In this article:

    August just became more hot; with great pleasure we —team Lenses— announce the immediate release of Lenses 2.1.
    Following an ambitious road-map, this version focuses on fortifying our SQL engine’s capabilities, the all-new global streaming topology graph and an improved user experience.

    Lenses SQL now supports ALL data formats

    The Lenses SQL streaming engine for Apache Kafka can now handle any type of
    serialization format, including the much requested Google’s Protobuf.

    Streaming XML and SQL

    Native support for streaming XML payloads. While assisting a financial institution to manage and process millions of
    continuously streaming XML messages, we introduced XML support to Lenses SQL queries. Lenses 2.1 brings
    this capability publicly available. Click here
    for an example on how you can now leverage streaming SQL on Kafka XML data.

    Google’s PROTOBUF or any other custom formats

    Avro and JSON payload types may be the most advertised options when it comes to
    serializing Kafka records. However, many companies rely
    on Google’s Protobuf or their
    own serializers. Here’s an example of running a bounded query for a
    topic containing records stored with Google’s Protobuf:

    proto topics

    The support for any serialization format extends to both bound and unbound streaming
    SQL in Lenses, hence joining and aggregating Protobuf data is as simple as
    working with JSON and Avro. Here is an example of a real time fraud detection (a
    very simple process) using topics storing data with Protobuf.

    proto processors

    Array support

    Your streaming SQL engine should fit your data structures, not the other way
    around. As such, array support was on our road-map from day one. Starting with
    this release, you can address arrays and their elements through the typical
    array syntax 

    devices[1].temperatures[2]
    . Of course this functionality
    covers all payload types (Avro, JSON, XML, Protobuf, custom), and is supported by
    both batch and streaming modes.

    array

    Topology graph supports your custom apps & micro-services

    Lenses Topology Graph offers a unique visualization of all your Kafka-native real-time data flows.
    We trust it will become your go-to place for monitoring all your data streaming pipelines,
    as it provides a unique high-level view of how your data moves in and out of Kafka.

    It is all about giving you control: To make sure things run as expected, to know and understand how your data is
    moving around and processed within the organization.
    We want you to be able to answer the following questions without breaking a sweat:

    • Where is my data flowing from?

    • Who and how is accessing and manipulating it?

    • Where is it flowing to?

    Until now, Lenses has been answering the question on where your data is originating from, where it is moving to
    as well as who is processing and how covering both Connectors and Kafka SQL processors.
    With this new release Lenses fully supports all your micro-services and data processors.

    A micro-service can be a simple Kafka consumer or producer, or even have a higher level of complexity using Kafka
    Streams, Akka Streams or even Apache Spark Streaming to handle real-time stream processing. A topology library supports all data processing frameworks, and examples
    are available on GitHub.

    With the interactive topology providing low latency metrics on each node, Lenses makes sure your real time data flow pipelines are operating in such a manner that meets business requirements. Every team can now take advantage of better control and visibility over the data flow pipelines, irrespective of the underlying technology, leading to a more mature approach to data movement and data operations.

    topology

    You can find more about monitoring your streaming apps on the topology section of our documentation

    Smarter SQL engine

    We made querying Apache Kafka even easier; Lenses SQL is now context aware. Since the earliest release, Lenses has been continuously identifying the payload types of Kafka topics. An additional set of keywords 

    _ktype
     and 
    _vtype 
    could be used to explicitly define the payload. This requirement is no more. You can still override the payload types via the _ktype/_vtype if needed, for example when avoiding deserialization to gain higher performance.

    Querying Apache Kafka with SQL is as simple as querying a traditional database.

    select lsql

    One can always set the topic payload types via the user interface. When there is not enough information to infer the payload
    type (when there’s no message yet on the topic, for example), or a custom serialization format is used,
    such as Protobuf, you will have to manually set the payload type once, via the topic page —or our cli tool—, as shown in the image below:

    serde settings

    Explore and query your data with ease

    Working with data probably means you write and execute SQL queries every day or even every other minute!
    Accessing your data with a single click and executing queries is now possible with the new SQL management page.

    This new screen gives you access to all available topics, but most importantly their schemas and fields to
    build queries. Lenses preserves your recent queries, and gives you the results in 3 different modes: tree, grid or raw data.
    You can also download the computed dataset for further analysis.

    studio sql

    Don’t forget that you can hook your queries to your code or your favorite tool with the Lenses SQL JDBC driver or any of our client libraries (go, python, redux).

    Enterprise ready

    Enterprise security and Data governance have always been a first class citizen in Lenses. The existing LDAP,
    Active Directory, SASL/SSL and Kerberos support have been further enhanced with additional enterprise security capabilities.

    Kerberos based Single Sign on (SSO) is the latest addition to our supported authentication methods for Lenses.

    This release also adds support for Kerberized schema registries (such as the one provided by HortonWorks).

    Other Improvements

    Under the hood, you will find many SQL streaming performance optimizations. The
    user experience has been significantly enhanced, with both a more responsive UI
    and usability improvements. You can now retrieve and review all logs from SQL
    processors that run in Kubernetes. Last but not least a totally revamped Lenses CLI
    and Python library are now available.

    Get the new version now!

    If you are running the Lenses environment for Developers, don’t forget to 

    docker pull
     to get the latest updates:

    docker pull landoop/kafka-lenses-dev:latest

    Download Lenses now:

    Downloads

    If you want to connect Lenses to your cluster contact us now for a demo and trial!

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