Upsolver
Contact Support
  • Welcome to Upsolver
  • Getting Started
    • Start using Upsolver for free
    • Get started as a Upsolver user
      • Upsolver in 5 minutes
        • Upsolver Quickstart in 5 minutes
          • Additional sandbox fun
        • Amazon Athena data output
        • MySQL (AWS RDS) data output
        • Local MySQL data output
      • Upsolver free training
        • Introduction to Upsolver
          • Transform and write data to Amazon Athena
          • Pre-aggregate data for efficiency and performance
          • UPSERT streaming data to Amazon Athena
      • Prerequisites for AWS deployment
      • AWS integration
      • Deploy Upsolver on your AWS account
      • Prerequisites for Azure Deployment
      • Azure Integration
        • Prerequisites for Azure Users
        • Log into Upsolver
        • Log into Azure & Authenticate
        • Set Up and Deploy Azure Resources
        • Delegate Resource Group, and Deploy Upsolver in Azure
        • Integrate Azure with Upsolver
    • Upsolver concepts
      • Deployment models
      • Upsolver components
      • Data ingestion
    • Upsolver Amazon AWS deployment guide
      • Private VPC
      • Upsolver VPC
      • AWS role permissions
      • VPC peering
    • Tutorials and FAQ
      • Tutorials
        • How To Re-process Data
        • Create an Amazon S3 data source
        • Create an Amazon Athena data output
        • Join multiple data streams for real-time analytics
        • Use Upsolver to index less data into Splunk
        • Upsert and delete use case
        • AWS S3 to Athena use case
        • Merge data use case
        • Full vs. Partial Inbound Data Records
      • FAQ
      • Infrastructure
        • What is a dry-run cluster?
    • Glossary
      • Language guide
        • SQL syntax reference
        • Functions
          • Aggregation Functions
            • APPROX_COUNT_DISTINCT
            • APPROX_COUNT_DISTINCT_EACH
            • AVG
            • AVG_EACH
            • AVG_TIME_SERIES
            • COLLECT_SET
            • COLLECT_SET_EACH
            • COUNT
            • COUNT(*)
            • COUNT_DISTINCT
            • COUNT_EACH
            • COUNT_IF
            • DECAYED_SUM
            • DYNAMIC_SESSIONS
            • FIRST
            • FIRST_ARRAY
            • FIRST_EACH
            • FIRST_TIME_SERIES
            • LAST
            • LAST_ARRAY
            • LAST_EACH
            • LAST_K
            • LAST_K_EACH
            • LAST_TIME_SERIES
            • MAX
            • MAX_BY
            • MAX_EACH
            • MAX_TIME_SERIES
            • MIN
            • MIN_BY
            • MIN_EACH
            • MIN_TIME_SERIES
            • SESSION_COUNT
            • STD_DEV
            • STD_DEV_EACH
            • STRING_MAX_EACH
            • STRING_MIN_EACH
            • SUM
            • SUM_EACH
            • SUM_TIME_SERIES
            • WEIGHTED_AVERAGE
          • Calculated functions
            • Aerospike functions
            • Array functions
            • Conditional functions
            • Date functions
            • External API functions
            • Filter functions
            • Numeric functions
            • Spatial functions
            • String functions
            • Structural functions
              • ZIP
            • Type conversion functions
      • Data formats
      • Data types and features
      • Database output options
      • Upsolver shards
      • Permissions list
      • Index
    • Troubleshooting
      • My CloudFormation stack failed to deploy
      • My private API doesn't start or I can't connect to it
        • Elastic IPs limit reached
        • EC2 Spot Instance not running
        • DNS cache
        • Security group not open
      • My compute cluster doesn't start
      • I can't connect to my Kafka cluster
      • I can't create an S3 data source
      • Data doesn't appear in Athena table
      • I get an exception when querying my Athena table
      • Unable to define a JDBC (Postgres) connection
  • Connecting data sources
    • Amazon AWS data sources
      • Amazon S3 data source
        • Quick guide: S3 data source
        • Full guide: S3 data source
      • Amazon Kinesis Stream data source
      • Amazon S3 over SQS data source
      • Amazon AppFlow data source
        • Setup Google Analytics client ID and client secret.
    • Microsoft Azure data sources
      • Azure Blob storage data source
      • Azure Event Hubs data source
    • Kafka data source
    • Google Cloud Storage data source
    • File upload data source
    • CDC data sources (Debezium)
      • MySQL CDC data source
        • Binlog retention in MySQL
      • PostgreSQL CDC database replication
    • JDBC data source
    • HDFS data source
    • Data source UI
    • Data source properties
  • Data outputs and data transformation
    • Data outputs
      • Amazon AWS data outputs
        • Amazon S3 data output
        • Amazon Athena data output
          • Quick guide: Athena data output
          • Full guide: Athena data output
          • Output all data source fields to Amazon Athena
        • Amazon Kinesis data output
        • Amazon Redshift data output
        • Amazon Redshift Spectrum data output
          • Connect Redshift Spectrum to Glue Data Catalog
        • Amazon SageMaker data output
      • Data lake / database data outputs
        • Snowflake data output
          • Upsert data to Snowflake
        • MySQL data output
        • PostgreSQL data output
        • Microsoft SQL Server data output
        • Elasticsearch data output
        • Dremio
        • PrestoDB
      • Upsolver data output
      • HDFS data output
      • Google Storage data output
      • Microsoft Azure Storage data output
      • Qubole data output
      • Lookup table data output
        • Lookup table alias
        • API Playground
        • Serialization of EACH aggregations
      • Kafka data output
    • Data transformation
      • Transform with SQL
        • Mapping data to a desired schema
        • Transforming data with SQL
        • Aggregate streaming data
        • Query hierarchical data
      • Work with Arrays
      • View outputs
      • Create an output
        • Modify an output in SQL
          • Quick guide: SQL data transformation
        • Add calculated fields
        • Add filters
        • Add lookups
          • Add lookups from data sources
          • Add lookups from lookup tables
          • Adding lookups from reference data
        • Output properties
          • General output properties
      • Run an output
      • Edit an output
      • Duplicate an output
      • Stop an output
      • Delete an output
  • Guide for developers
    • Upsolver REST API
      • Create a data source
      • Modify a data source
      • API content formats
    • CI/CD on Upsolver
  • Administration
    • Connections
      • Amazon S3 connection
      • Amazon Kinesis connection
      • Amazon Redshift connection
      • Amazon Athena connection
      • Amazon S3 over SQS connection
      • Google Storage connection
      • Azure Blob storage connection
      • Snowflake connection
      • MySQL connection
      • Elasticsearch connection
      • HDFS connection
      • Qubole connection
      • PostgreSQL connection
      • Microsoft SQL Server connection
      • Spotinst Private VPC connection
      • Kafka connection
    • Clusters
      • Cluster types
        • Compute cluster
        • Query cluster
        • Local API cluster
      • Monitoring clusters
      • Cluster tasks
      • Cluster Elastic IPs
      • Cluster properties
      • Uploading user-provided certificates
    • Python UDF
    • Reference data
    • Workspaces
    • Monitoring
      • Credits
      • Delays In Upsolver pipelines
      • Monitoring reports
        • Monitoring system properties
        • Monitoring metrics
    • Security
      • IAM: Identity and access management
        • Manage users
        • Manage groups
        • Manage policies
      • Git integration
      • Single sign-on with SAML
        • Microsoft Azure AD with SAML sign-on
        • Okta with SAML sign-on
        • OneLogin with SAML sign-on
      • AMI security updates
  • Support
    • Upsolver support portal
  • Change log
  • Legal
Powered by GitBook
On this page
  • Create an Athena data output and define a data source
  • Join two data streams together and perform data transformation
  • Define Athena output parameters
  • Check output data and run analytics
  • What’s next?

Was this helpful?

  1. Getting Started
  2. Tutorials and FAQ
  3. Tutorials

Join multiple data streams for real-time analytics

This article provides a walkthrough on how to join multiple data streams for real-time analytics.

PreviousCreate an Amazon Athena data outputNextUse Upsolver to index less data into Splunk

Last updated 4 years ago

Was this helpful?

Before performing a join on multiple data streams, you must have already and .

Performing a join on multiple data streams is easy with Upsolver.

This guide provides the instructions on joining:

  • impressions: primary data source with ad campaign information

  • clicks: secondary data stream tracking number of clicks on an ad

Note: All clicks will be associated with an ad impression, but not all ad impressions will result in clicks.

Create an Athena data output and define a data source

1. Click on Outputs on the left and then New on the right upper corner.

2. Select Amazon Athena as the data output.

3. Click Add to add as many data sources as you need. Click Next to continue.

Join two data streams together and perform data transformation

1. Select the SQL window from the upper right hand corner.

2. The sample SQL below performs a LEFT OUTER JOIN between impressions and clicks data streams.

Behind the scenes, the LEFT OUTER JOIN is creating a lookup table, enabling users to index data by a set of keys and then retrieve the results in milliseconds.

Sample SQL
SELECT data.id AS impression_id, 
    data.win_timestamp AS impression_time, 
    data.campaign_id AS campaign_id, 
    data.exch_user AS user_id, 
    IF_ELSE(click_data.click_time IS NULL, 0, 1) AS is_click 
        -- if click_time exists returns 1, else returns 0
FROM Impressions LEFT OUTER JOIN 
    (SELECT data.id AS imp_id, 
        LAST(data.click_timestamp) AS click_time 
            -- last click_timestamp is the click_time
    FROM Clicks GROUP BY data.id) 
AS click_data WAIT 10 MINUTES ON click_data.imp_id = data.id 
    -- wait for 10 minutes before performing the join since clicks usually arrive after impressions.

Define Athena output parameters

1. Define storage, database, and table information for your Athena environment and click Next.

2. Define the compute cluster that you would like to use and the time range of the data you would like to output.

Keep in mind that setting Ending At to Never means the output will be a continuous stream.

3. Click Deploy.

Check output data and run analytics

1. Check to make sure the output data is up to date by clicking on the Progress tab.

2. Run a query in Athena to make sure you get the correct results.

Athena query
SELECT campaign_id, 
    SUM(is_click)/COUNT(*) AS CTR
        -- to get the click through rate: 
        -- divide the sum of clicks for a campaign with the total number of impressions 
FROM impression_clicks
GROUP BY campaign_id

What’s next?

Read more about Upsolver lookup tables .

here
Use Upsolver to index less data into Splunk
deployed Upsolver
created data sources