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

Was this helpful?

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

Merge data use case

This article outlines a use case in which you merge data from two sources together to create a final output.

PreviousAWS S3 to Athena use caseNextFull vs. Partial Inbound Data Records

Last updated 4 years ago

Was this helpful?

A very common use case is merging data from a data stream (A) with a reference data source (B). This requires you to use a field to lookup (and merge) data from the reference data source (B) with the data stream (A) and then save the resulting data in the output.

This can be achieved by adding a lookup to the output and specifying the matching key. Any data brought in from the data source (B) comes in via an aggregation in the lookup.

For example, you can use the LAST aggregation function to select the last value of a field within a time window. This can also be used to look up user information that is stored in a user data table—that is, given the USER_ID, look up the USER_DETAIL, USER_DETAIL2, and so on.

Required Level of Expertise

  • Intermediate

Add a lookup

1. On the Outputs page, select the desired output and click Edit (or ).

2. Click Add Lookup and select the lookup source (e.g. an existing data source or lookup table). Then click Next.

3. In Join Fields, select the field to join to in data source (B) (e.g.USER_ID). The matching field in data stream (A) is selected automatically.

Note: The field on the left is the field in data source (B) that we are looking up from. The field on the right is the key from data stream (A).

4. Add aggregations; for example:

  • LAST(USER_ID)

  • LAST(USER_DETAIL1)

  • LAST(USER_DETAIL2)

5. Set the Time Frame to infinite, by entering -10000 in the From field. This ensures you can access all the data irrespective of when it was written.

6. Select Use Full History to treats the data source (B) as a reference data table. This is useful if the latest view of the data is required, and the actual time that the data was written is irrelevant.

7. Enter an Alias for the lookup and click Save.

Toggle from the UI to SQL view to see the JOIN statement (it can appear as part of a WITH statement or inline).

8. Click Run and fill in the required details to deploy the output. See:

create a new output
Run an output