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For Snowflake projects, the HubSpot Load connector supersedes the HubSpot Query connector, which is no longer available for new pipelines. Existing pipelines that use the HubSpot Query connector will continue to work as expected.Databricks and Amazon Redshift projects should continue to use the HubSpot Query connector.
The Load component lets you connect to your account and configure a query to load data from the API. You can select the data source, choose the fields to include in your query, and apply filters to refine your results. You can also specify a row limit to control the number of records returned. The results of your query can be loaded into your destination as a new table or can replace an existing table. You can also configure incremental load settings to load only new or updated records since the last load. Your destination can be your connected cloud data warehouse or a cloud storage location. You can also configure advanced settings to control the output encoding, key sanitization strategy, and other options. If the component requires access to a cloud provider (AWS, Azure, or Google Cloud), it will use the cloud credentials associated with your environment to access resources. To stage data to Azure Blob Storage, the Azure credentials associated with your environment must be assigned the Storage Blob Data Contributor role. For more information, read User assigned with the Storage Blob Data Contributor role.

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Properties

Reference material is provided below for the Connect, Configure, Destination, and Advanced Settings properties.
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string
required
A human-readable name for the component.

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Connect

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drop-down
required
Choose OAuth 2.0 Authorization Code or API key as the authentication method.
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drop-down
required
Choose your OAuth connection from the drop-down.Click Manage to navigate to the OAuth connections list to review OAuth connections and to add new connections. Read OAuth to learn how to create an OAuth connection.
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drop-down
required
This parameter is only available when you choose API Key as the authentication method.Choose the secret definition that represents your credentials for this connector.If you have not already saved your credentials for this connector as a secret definition, click Add secret to create a secret definition representing these credentials. Read Secrets and secret definitions for details about creating a secret definition.Read HubSpot authentication guide to learn how to obtain a Private App token.
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column editor
  • Parameter: A JDBC parameter supported by the database driver. The available parameters are explained in data model. Manual setup is not usually required, since sensible defaults are assumed.
  • Value: A value for the given parameter.
Click the Text Mode toggle at the bottom of the Connection Options dialog to open a multi-line editor that lets you add items in a single block. For more information, read Text mode.To use grid variables, select the Use Grid Variable checkbox at the bottom of the Connection Options dialog.

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Configure

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drop-down
required
  • Full Load: Load all data from the data source on every pipeline run.
  • Incremental Load: Load only new or updated data since the last successful pipeline run using a high-water mark column.
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drop-down
required
  • Basic: Configure data selection using the Data Source, Data Selection, Data Source Filter, Combine Filters, and Row Limit properties.
  • Advanced: Write your own SQL query using the SQL Query property.
  • Incremental: Use incremental data loading with a high-water mark column. Available when Load Type is set to Incremental Load.
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code editor
required
Enter an SQL-like SELECT query to retrieve the data you want. This query must be written in the SQL accepted by your cloud data warehouse. Treat collections as table names, and fields as columns. Only available in Advanced mode.For more information, read the SELECT query documentation for your cloud data warehouse:
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drop-down
required
Select the schema to use when browsing available data sources. Only available for Snowflake destinations.
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drop-down
required
Select the data source to query from. Available when Mode is set to Basic.
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object selector
required
Select the columns to fetch from the selected data source. Only available in Basic mode.To use grid variables, toggle Use Grid Variable on. For more information, read Grid variables.
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grid
Filter the rows returned from the data source. Available when Mode is set to Basic.
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drop-down
required
Choose how to combine multiple filters. Select AND to return rows matching all filters, or OR to return rows matching any filter. Available when Mode is set to Basic.
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integer
The maximum number of rows to return from the data source. Leave blank to return all rows. Available when Mode is set to Basic.
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drop-down
required
Select the column to use as the high-water mark for incremental loading. Available when Load Type is set to Incremental Load.

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Destination

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drop-down
required
Select the destination for your data. This is either in Snowflake as a table or as files in cloud storage.
  • Snowflake: Load your data into a table in Snowflake. The data must first be staged via Snowflake or a cloud storage solution.
  • Cloud Storage: Load your data directly into files in your preferred cloud storage location. The format of these files can differ between source systems and will not have a file extension so we suggest inspecting the output to determine the format of the data.
When Incremental Load is selected, Cloud Storage is not supported as a destination. Only warehouse destinations (Snowflake or Google BigQuery) are available for incremental loads.
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drop-down
required
The Snowflake warehouse used to run the queries. The special value [Environment Default] uses the warehouse defined in the environment. Read Overview of Warehouses to learn more.
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drop-down
required
The Snowflake database to access. The special value [Environment Default] uses the database defined in the environment. Read Databases, Tables and Views - Overview to learn more.
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drop-down
required
The Snowflake schema. The special value [Environment Default] uses the schema defined in the environment. Read Database, Schema, and Share DDL to learn more.
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string
required
The name of the table to be created in your Snowflake database. You can use a Table Input component in a transformation pipeline to access and transform this data after it has been loaded.
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drop-down
required
Define what happens if the table name already exists in the specified destination. Only available when Full Load is selected.
  • Replace: If the specified table name already exists, that table will be destroyed and replaced by the table created during this pipeline run.
  • Truncate and Insert: Each time the pipeline runs, two operations are performed: first, the table is truncated, meaning all existing rows are deleted. Then, your new rows are inserted. The table itself is never destroyed and recreated.
  • Fail if Exists: If the specified table name already exists, this pipeline will fail to run.
  • Append: If the specified table name already exists, then the data is inserted without altering or deleting the existing data in the table. It’s appended onto the end of the existing data in the table. If the specified table name doesn’t exist, then the table will be created, and your data will be inserted into the table.
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object selector
Select one or more columns to use as the table’s primary key. If you select multiple columns, the component creates a composite primary key using the combination of the selected columns.Leave this blank to create the table without a primary key.When using Incremental Load, if you select a primary key, the loaded data will be merged with your existing data. If you don’t select a primary key, the loaded data will be appended to your existing data.
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boolean
required
  • Yes: Staged files will be destroyed after data is loaded. This is the default setting.
  • No: Staged files are retained in the staging area after data is loaded.
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drop-down
required
Use the drop-down menu to choose where the data is staged before being loaded into your Snowflake table.
  • Amazon S3: Stage your data on an AWS S3 bucket.
  • Snowflake: Stage your data on a Snowflake internal stage.
  • Azure Storage: Stage your data in an Azure Blob Storage container.
  • Google Cloud Storage: Stage your data in a Google Cloud Storage bucket.
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drop-down
required
Select the Snowflake internal stage type. Use the Snowflake links provided to learn more about each type of stage.
  • User: Each Snowflake user has a user stage allocated to them by default for file storage. You may find the user stage convenient if your files will only be accessed by a single user, but need to be copied into multiple tables.
  • Named: A named stage provides high flexibility for data loading. Users with the appropriate privileges on the stage can load data into any table. Furthermore, because the stage is a database object, any security or access rules that apply to all objects will apply to the named stage.
Named stages can be altered and dropped. User stages cannot.
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drop-down
required
Select your named stage. Read Creating a named stage to learn how to create a new named stage.
You can’t select a named stage if its name includes special characters or spaces.

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Advanced Settings

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drop-down
required
Choose whether to automatically log debug information about your load. These logs can be found in the task history and should be included in support requests concerning the component. Turning this on will override any debugging connection options.
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drop-down
required
The level of verbosity with which your debug information is logged. Levels above 1 can log huge amounts of data and result in slower execution. These logs can be found in the Message field of the task details after pipeline execution and should be included in support requests concerning the component.
  1. Will log the query, the number of rows returned by it, the start of execution and the time taken, and any errors.
  2. Will log everything included in Level 1, plus cache queries and additional information about the request, if applicable.
  3. Will additionally log the body of the request and the response.
  4. Will additionally log transport-level communication with the data source. This includes SSL negotiation.
  5. Will additionally log communication with the data source, as well as additional details that may be helpful in troubleshooting problems. This includes interface commands.
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boolean
required
Converts common strings that represent null into a null value. This is case-sensitive and works with the following strings: "", “NULL”, “NUL”, “Null”, “null”. The default is No.
This parameter is only applicable when using Snowflake as your destination.
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boolean
required
When Yes, remove leading and trailing characters from a string column. The default is No.
This parameter is only applicable when using Snowflake as your destination.

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Data model

The JDBC driver for this component models HubSpot APIs as relational tables, views, and stored procedures, which are documented in the data model. You’ll also find API limitations and requirements. The connection option SupportEnhancedSQL is set to true by default and typically circumvents most API limitations. This connector also allows you to query system tables in Advanced mode. To see the available system tables in the data model, read the System Tables section of the data model. For more information about using system tables, read our System tables guide.