Integrate the BigML API with the MySQL API

Setup the BigML API trigger to run a workflow which integrates with the MySQL API. Pipedream's integration platform allows you to integrate BigML and MySQL remarkably fast. Free for developers.

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Popular Ways to Connect BigML with MySQL#

Execute Raw Query with MySQL API on New Model Created from BigML API

BigML + MySQL

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Execute Raw Query with MySQL API on New Prediction Made from BigML API

BigML + MySQL

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Create Batch Prediction with BigML API on New Column from MySQL API

MySQL + BigML

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Create Batch Prediction with BigML API on New or Updated Row from MySQL API

MySQL + BigML

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Create Batch Prediction with BigML API on New Row (Custom Query) from MySQL API

MySQL + BigML

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Popular BigML and MySQL Triggers#

New Model Created from the BigML API

Emit new event for every created model. See docs here.

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New Prediction Made from the BigML API

Emit new event for every made prediction. See docs here.

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New Column from the MySQL API

Emit new event when you add a new column to a table. See the docs here

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New or Updated Row from the MySQL API

Emit new event when you add or modify a new row in a table. See the docs here

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New Row from the MySQL API

Emit new event when you add a new row to a table. See the docs here

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Popular BigML and MySQL Actions#

Create Batch Prediction with the BigML API

Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.

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Execute SQL Query with the MySQL API

Execute a custom MySQL query. See our docs to learn more about working with SQL in Pipedream.

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Create Model with the BigML API

Create a model based on a given source ID, dataset ID, or model ID. See the docs.

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Create Row with the MySQL API

Adds a new row. See the docs here

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Create Source (Remote URL) with the BigML API

Create a source with a provided remote URL that points to the data file that you want BigML to download for you. See the docs.

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Overview of BigML#

The BigML API offers a suite of machine learning tools that enable the creation and management of datasets, models, predictions, and more. It's a powerful resource for developers looking to incorporate machine learning into their applications. Within Pipedream, you can leverage the BigML API to automate workflows, process data, and apply predictive analytics. By connecting BigML to other apps in Pipedream, you can orchestrate sophisticated data pipelines that react to events, perform analyses, and take action based on machine learning insights.

Connect BigML#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    bigml: {
      type: "app",
      app: "bigml",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://bigml.io/andromeda/source`,
      params: {
        username: `${this.bigml.$auth.username}`,
        api_key: `${this.bigml.$auth.api_key}`,
      },
    })
  },
})

Overview of MySQL#

The MySQL application on Pipedream enables direct interaction with your MySQL databases, allowing you to perform CRUD operations—create, read, update, delete—on your data with ease. You can leverage these capabilities to automate data synchronization, report generation, and event-based triggers that kick off workflows in other apps. With Pipedream's serverless platform, you can connect MySQL to hundreds of other services without managing infrastructure, crafting complex code, or handling authentication.

Connect MySQL#

import mysql from '@pipedream/mysql';

export default defineComponent({
  props: {
    mysql,
  },
  async run({steps, $}) {
    // Component source code:
    // https://github.com/PipedreamHQ/pipedream/tree/master/components/mysql

    const queryObj = {
      sql: "SELECT NOW()",
      values: [], // Ignored since query does not contain placeholders
    };
    return await this.mysql.executeQuery(queryObj);
  },
});

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