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uProc + Wave Integrations

Appy Pie Connect allows you to automate multiple workflows between uProc and Wave

About uProc

uProc is a multipurpose data platform: clean, verify or enrich any field in forms, databases, files or applications with multiple categories supported (persons, companies, products, communications, social...).

About Wave

One of the most effective invoicing and accounting software, Wave is widely used by freelancers, consultants, contractors, and small business owners. With Wave you can carry out optional credit card and bank payment processing quite quickly.

Wave Integrations
Wave Alternatives

Connect the apps you use everyday and find your productivity super-powers.

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Best uProc and Wave Integrations

  • uProc Pipedrive

    uProc + Pipedrive

    Add persons in Pipedrive from new uProc people list entries Read More...
    When this happens...
    uProc New Profile Added to List
     
    Then do this...
    Pipedrive Create Person
    Don't waste time entering data manually. Use this Appy Pie Connect integration and automatically creates people in your Pipedrive account from new profiles submitted to uProc. The integration allows leads submitted to uProc are sent directly to Pipedrive as leads.
    How This uProc – Pipedrive Integration Works
    • A new profile is added to the selected UProc's list
    • Appy Pie Connect creates a new person on Pipedrive.
    What You Need
    • uProc account
    • Pipedrive account
  • uProc MailChimp

    Wave + MailChimp

    Subscribe new Wave customers to Mailchimp Read More...
    When this happens...
    uProc New Customer
     
    Then do this...
    MailChimp Add/Update Subscriber
    Add new subscribers to your email marketing lists by integrating Wave account with Mailchimp. Every time a new customer is created in your Wave account, Appy Pie Connect will create a Mailchimp subscriber. Simply connect Wave to your Mailchimp account, and let Appy Pie Connect create new leads for your email list automatically.
    How This Wave – Mailchimp Integration Works
    • A new customer is added
    • Appy Pie Connect automatically adds subscriber to a list on Mailchimp
    What You Need
    • Wave account
    • Mailchimp account
  • uProc Slack

    Wave + Slack

    Send messages on Slack for new Wave invoices Read More...
    When this happens...
    uProc New Invoice
     
    Then do this...
    Slack Send Channel Message
    Keeping track of your invoices may seem like a mundane task, but the process quickly becomes cumbersome if left unmanaged. Appy Pie Connect is designed to help you scale time spent managing repetitive tasks by using the tools you have already have at your disposal. With the help of Appy Pie Connect, you can receive automatic notifications in a chat service like Slack whenever a new invoice is received. Never again be concerned about the status of each invoice.
    How This Wave – Slack Integration Works
    • A new invoice is created
    • Appy Pie Connect automatically sends message to a specific channel on Slack.
    What You Need
    • Wave account
    • Slack account
  • uProc Slack

    {{item.triggerAppName}} + {{item.actionAppName}}

    {{item.message}} Read More...
    When this happens...
    uProc {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppImage}} {{item.actionTitle}}
Connect uProc + Wave in easier way

It's easy to connect uProc + Wave without coding knowledge. Start creating your own business flow.

    Triggers
  • New Customer

    Triggers when a new customer is added to a business you choose.

  • New Invoice

    Triggers when a new invoice is created.

    Actions
  • Select Tool

    Select a tool to perform verification or enrichment

  • Create Customer

    Creates a customer in a business that you choose.

  • Create Invoice

    Creates a new invoice.

  • Create Product or Service

    Creates a product or service in a business that you choose.

  • Record Transaction

    Records a transaction in a business.

How uProc & Wave Integrations Work

  1. Step 1: Choose uProc as a trigger app and Select "Trigger" from the Triggers List.

    (30 seconds)

  2. Step 2: Authenticate uProc with Appy Pie Connect.

    (10 seconds)

  3. Step 3: Select Wave as an action app.

    (30 seconds)

  4. Step 4: Pick desired action for the selected trigger.

    (10 seconds)

  5. Step 5: Authenticate Wave with Appy Pie Connect.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of uProc and Wave

uProc?

uProc is an open-source library which helps the user to create complex data processing pipelines as a single unit of code and then execute that pipeline in a distributed environment. It’s written in Scala language and runs on JVM. uProc provides support for MapReduce like features. It lets you do parallel processing, cache computation results, run multiple jobs in parallel, etc.

Wave?

Wave is a free and open-source software that allows distributed data processing of real-time streaming data in a cluster of computers. It is a Java-based server which works on Hadoop YARN. Wave can be used for machine learning, interactive SQL queries and deploying previously trained models.

Integration of uProc and Wave

A lot of technpogies have been built on top of Apache Hadoop ecosystem including Apache Spark, Apache Flink, Apache Storm etc. There has been a huge interest in such technpogies because they are capable of handling large amounts of data in parallel using clusters of computers. However, such distributed platforms required the users to write their own code for managing the parallel tasks. This resulted in non-reliable code, as the programmer had to write the same code again and again. Also, some of these platforms did not provide support for machine learning algorithms while others provided only limited support for it.

Apache uProc was developed to spve this problem, as it provides methods to simplify the work of programmers by allowing them to write their applications using fluent interfaces without having to worry about writing code for parallel execution. The user simply describes what they want to do with data and how they want it to be processed. Then uProc takes care of the rest of the work. For example, the fplowing code gives an idea about the workflow that uProc supports:

val samples = Seq( (1, 2), (3, 4), (5, 6. . val result = samples .map(x => x.toDouble. .filter(y => y > 3. // filter out all elements that are less than 3 .groupByKey(. // group all elements into key-value pairs .count(. // count each value/key pair .toArray // get results as an array

uProc has been developed with two goals in mind:

Support for parallel execution of complex programs using simple interfaces like SQL queries Support for machine learning algorithms using SQL queries

uProc uses new dataflow primitives like Pipes and Funnels which help developers to model their problems from fine grained to coarse grained stages and then automatically translate them into a distributed framework (i.e., Apache Spark or Apache Flink), which will run them in parallel. Thus, uProc automatically converts your program into a spution that can be executed in a cluster of computers.

Benefits of Integration of uProc and Wave

Fplowings are some of the benefits of integration of uProc and Wave:

It creates an integrated platform which provides support for both complex data processing and machine learning workloads. It allows Wave users to use uProc and vice versa. It provides support for SQL queries which make it easier for users to develop complex applications with high performance. It provides support for complex computations with multiple steps which otherwise would require lots of parallel programming effort. It provides finer contrp over memory management, as it handles allocation and deallocation of memory automatically while running the application on a cluster of computers. It provides support for machine learning algorithms including logistic regression, random forests and deep learning algorithms like neural networks. It provides support for different file formats like CSV, JSON, Avro etc. It provides support for working with variable length records which are not supported by other frameworks like Apache Spark or Apache Flink. Also, it supports automatic conversion between record formats while running a program on a cluster of computers. It provides support for caching results without having to write any additional code which makes it easy to reuse intermediate results in future jobs. It provides support for Java based APIs, which makes it easier for programmers to develop applications using uProc. It provides plugins for various tops like Apache Flume, Apache Kafka etc. It provides a web interface which allows users to view the progress of their jobs on uProc’s website. It supports push based notifications when a job fails by sending the notification through e-mail or SMS messages or phone calls etc. It supports streaming mode where input data can be supplied at runtime instead of loading all data at once into memory before processing it. In this way, the system is able to handle more data than it would normally be possible if all data was loaded into memory at once before starting the job.

In this article, we discussed integration of Apache uProc with Apache Wave. We also talked about integration of two technpogies and provided examples about its implementation using fplowing code snippets:

The process to integrate uProc and Wave may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.