Upsolver
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Local MySQL data output
Process streaming data from end-to-end within 10 minutes. The data source is an Amazon S3 bucket (updated continuously). Upsolver processes the data and loads to your local MySQL environment.
To help you get started with Upsolver, you can try it out for free. You can choose between Upsolver Dedicated Compute and Community subscriptions. Both options give you free Upsolver units (UUs), units of processing capability per hour based on VM instance type.

Create a data source

1. Click on DATA SOURCES > NEW to connect to various data sources. Upsolver works with both streaming and static data sources.
2. Click on SELECT next to Amazon S3 data source. There are many data sources to choose from. The Quickstart uses pre-populated mobile data.
3. Choose BUCKET > upsolver-tutorials-mobile-users by clicking on the dropdown box. Fill in FOLDER > data and DATE PATTERN > yyyy/MM/dd/HH/ click on CONTINUE. Upsolver automatically verifies the files in the bucket and displays blue checkmarks next to the file name.
4. Upsolver automatically parses the data and displays a sample of the data that you’re working with. You can expand each record to view each event in a formatted view.
5. Click on CREATE to complete the Amazon S3 Data Source. Notice the schema is automatically generated and data statistics are also displayed.

Create a data output

1. Click on NEW OUTPUT on the upper right corner. (You can also get to the output screen by clicking on OUTPUTS > NEW)
2. Choose MySQL output by clicking on SELECT. We’re going to use MySQL as our output for this tutorial. You can output to any Upsolver data outputs.
3. Enter gaming as the name of the output. Leave everything as default and click on NEXT.
4. Expand the payload field. Add a field to your output by clicking on the + sign next to eventName. The field that we’re adding is. data.payload.eventName.

Data transformation

1. Rename the fields by clicking on the field under SCHEMA COLUMN and rename payload.eventname to event_name
2. Transform data.clientEventTime to from unix epoch to human readable format in UTC. Click on Add Calculated Field on the upper left and find the TO_DATE function, then click on SELECT. Enter data.clientEventTime in the DATETIME box and give the field a NAME called event_time. Click on PREVIEW to make sure the date looks right and click on SAVE.
Click on Add Calculated Field
Find the TO_DATE() function and click on SELECT
Convert data.clientEventTime and to human readable format in UTC. Click on PREVIEW and SAVE.
3. Add event_time to your output by clicking on + next to the field.
4. Add a count for each event by clicking on Make Aggregated > OK > Add Aggregation. Click on SELECT next to COUNT (*) and click on SAVE.
Click on Make Aggregated
Click OK
Click on Add Aggregation and SELECT COUNT(*)
Click on SAVE
Click over to the SQL tab on the upper right hand corner. Keep in mind all changes that are made in the SQL view will also be represented in the UI view and vice-versa. You can see the work from the UI automatically generated a SELECT statement. Click on PREVIEW to ensure data looks correct.

Connect to MySQL and start streaming

1. Click on RUN on the upper right corner and choose Create a new MySQL Connection from the MySQL Connection dropdown.
2. (Optional) Setup a local MySQL environment if you don’t have an existing environment.
If you don’t have an existing MySQL connection, you can install it locally on your computer: download and install the MySQL Community Edition. Optionally, you can also download MySQL workbench as well. Keep in mind that other outputs will require integrations with your own AWS environment.
    Run the following commands in your MySQL environment.
1
set global local_infile = on;
2
CREATE database dev;
Copied!
    After MySQL is running locally, use ngrok to start a TCP tunnel forwarding to your local port 3306 by running ./ngrok tcp 3306 You will have the forwarding information below:
3. Define MySQL Connection in the following format (include the ngrok forwarding url from above) and click on CREATE
    CONNECTION STRING: jdbc:mysql://2.tcp.ngrok.io:13763/dev?useUnicode=true&useJDBCCompliantTimezoneShift=true&useLegacyDatetimeCode=false&serverTimezone=UTC
    USER NAME: root
    PASSWORD: <mysql password>
    NAME: mysql-local
4. Select OUTPUTS > gaming > Run and choose the connection that you just defined as MYSQL CONNECTION. Choose dev (make sure this database exists in your MySQL environment) under SCHEMA and TABLE NAME > gaming. Click on NEXT.
5. Use the sliding bar to only load from the data from last day click on DEPLOY. Keep in mind that ENDING AT set as Never means it's a continuous data stream. Click on OK if a warning appears.
6. Upsolver starts outputting the data to MySQL. You can keep track of the output status by clicking on PROGRESS. Wait for a moment for the data to output.

Verify your data in MySQL

Last modified 10mo ago