- Introduction
- Getting Started
- Creating an Account in Hevo
- Subscribing to Hevo via AWS Marketplace
-
Connection Options
- Connecting Through SSH
- Connecting Through Reverse SSH Tunnel
- Connecting Through VPN
- Connecting Through Mongo PrivateLink
- Connecting Through AWS Transit Gateway
- Connecting Through AWS VPC Endpoint
- Connecting Through AWS VPC Peering
- Using Google Account Authentication
- How Hevo Authenticates Sources and Destinations using OAuth
- Reauthorizing an OAuth Account
- Familiarizing with the UI
- Creating your First Pipeline
- Data Loss Prevention and Recovery
- Data Ingestion
- Data Loading
- Loading Data in a Database Destination
- Loading Data to a Data Warehouse
- Optimizing Data Loading for a Destination Warehouse
- Deduplicating Data in a Data Warehouse Destination
- Manually Triggering the Loading of Events
- Scheduling Data Load for a Destination
- Loading Events in Batches
- Data Loading Statuses
- Data Spike Alerts
- Name Sanitization
- Table and Column Name Compression
- Parsing Nested JSON Fields in Events
- Pipelines
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
- Working with Pipelines
- Managing Objects in Pipelines
- Pipeline Jobs
-
Transformations
-
Python Code-Based Transformations
- Supported Python Modules and Functions
-
Transformation Methods in the Event Class
- Create an Event
- Retrieve the Event Name
- Rename an Event
- Retrieve the Properties of an Event
- Modify the Properties for an Event
- Fetch the Primary Keys of an Event
- Modify the Primary Keys of an Event
- Fetch the Data Type of a Field
- Check if the Field is a String
- Check if the Field is a Number
- Check if the Field is Boolean
- Check if the Field is a Date
- Check if the Field is a Time Value
- Check if the Field is a Timestamp
-
TimeUtils
- Convert Date String to Required Format
- Convert Date to Required Format
- Convert Datetime String to Required Format
- Convert Epoch Time to a Date
- Convert Epoch Time to a Datetime
- Convert Epoch to Required Format
- Convert Epoch to a Time
- Get Time Difference
- Parse Date String to Date
- Parse Date String to Datetime Format
- Parse Date String to Time
- Utils
- Examples of Python Code-based Transformations
-
Drag and Drop Transformations
- Special Keywords
-
Transformation Blocks and Properties
- Add a Field
- Change Datetime Field Values
- Change Field Values
- Drop Events
- Drop Fields
- Find & Replace
- Flatten JSON
- Format Date to String
- Format Number to String
- Hash Fields
- If-Else
- Mask Fields
- Modify Text Casing
- Parse Date from String
- Parse JSON from String
- Parse Number from String
- Rename Events
- Rename Fields
- Round-off Decimal Fields
- Split Fields
- Examples of Drag and Drop Transformations
- Effect of Transformations on the Destination Table Structure
- Transformation Reference
- Transformation FAQs
-
Python Code-Based Transformations
-
Schema Mapper
- Using Schema Mapper
- Mapping Statuses
- Auto Mapping Event Types
- Manually Mapping Event Types
- Modifying Schema Mapping for Event Types
- Schema Mapper Actions
- Fixing Unmapped Fields
- Resolving Incompatible Schema Mappings
- Resizing String Columns in the Destination
- Schema Mapper Compatibility Table
- Limits on the Number of Destination Columns
- File Log
- Troubleshooting Failed Events in a Pipeline
- Mismatch in Events Count in Source and Destination
- Audit Tables
- Activity Log
-
Pipeline FAQs
- Can multiple Sources connect to one Destination?
- What happens if I re-create a deleted Pipeline?
- Why is there a delay in my Pipeline?
- Can I change the Destination post-Pipeline creation?
- Why is my billable Events high with Delta Timestamp mode?
- Can I drop multiple Destination tables in a Pipeline at once?
- How does Run Now affect scheduled ingestion frequency?
- Will pausing some objects increase the ingestion speed?
- Can I see the historical load progress?
- Why is my Historical Load Progress still at 0%?
- Why is historical data not getting ingested?
- How do I set a field as a primary key?
- How do I ensure that records are loaded only once?
- Events Usage
- Sources
- Free Sources
-
Databases and File Systems
- Data Warehouses
-
Databases
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Elasticsearch
-
MongoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
-
Troubleshooting MongoDB
-
Errors During Pipeline Creation
- Error 1001 - Incorrect credentials
- Error 1005 - Connection timeout
- Error 1006 - Invalid database hostname
- Error 1007 - SSH connection failed
- Error 1008 - Database unreachable
- Error 1011 - Insufficient access
- Error 1028 - Primary/Master host needed for OpLog
- Error 1029 - Version not supported for Change Streams
- SSL 1009 - SSL Connection Failure
- Troubleshooting MongoDB Change Streams Connection
- Troubleshooting MongoDB OpLog Connection
-
Errors During Pipeline Creation
- SQL Server
-
MySQL
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Generic MySQL
- Google Cloud MySQL
- MariaDB MySQL
-
Troubleshooting MySQL
-
Errors During Pipeline Creation
- Error 1003 - Connection to host failed
- Error 1006 - Connection to host failed
- Error 1007 - SSH connection failed
- Error 1011 - Access denied
- Error 1012 - Replication access denied
- Error 1017 - Connection to host failed
- Error 1026 - Failed to connect to database
- Error 1027 - Unsupported BinLog format
- Failed to determine binlog filename/position
- Schema 'xyz' is not tracked via bin logs
- Errors Post-Pipeline Creation
-
Errors During Pipeline Creation
- MySQL FAQs
- Oracle
-
PostgreSQL
- Amazon Aurora PostgreSQL
- Amazon RDS PostgreSQL
- Azure PostgreSQL
- Generic PostgreSQL
- Google Cloud PostgreSQL
- Heroku PostgreSQL
-
Troubleshooting PostgreSQL
-
Errors during Pipeline creation
- Error 1003 - Authentication failure
- Error 1006 - Connection settings errors
- Error 1011 - Access role issue for logical replication
- Error 1012 - Access role issue for logical replication
- Error 1014 - Database does not exist
- Error 1017 - Connection settings errors
- Error 1023 - No pg_hba.conf entry
- Error 1024 - Number of requested standby connections
- Errors Post-Pipeline Creation
-
Errors during Pipeline creation
- PostgreSQL FAQs
- Troubleshooting Database Sources
- File Storage
- Engineering Analytics
- Finance & Accounting Analytics
-
Marketing Analytics
- ActiveCampaign
- AdRoll
- Amazon Ads
- Apple Search Ads
- AppsFlyer
- CleverTap
- Criteo
- Drip
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Freshsales
- Google Ads
- Google Analytics
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- HubSpot
- Instagram Business
- Klaviyo v2
- Lemlist
- LinkedIn Ads
- Mailchimp
- Mailshake
- Marketo
- Microsoft Ads
- Onfleet
- Outbrain
- Pardot
- Pinterest Ads
- Pipedrive
- Recharge
- Segment
- SendGrid Webhook
- SendGrid
- Salesforce Marketing Cloud
- Snapchat Ads
- SurveyMonkey
- Taboola
- TikTok Ads
- Twitter Ads
- Typeform
- YouTube Analytics
- Product Analytics
- Sales & Support Analytics
- Source FAQs
- Destinations
- Familiarizing with the Destinations UI
- Cloud Storage-Based
- Databases
-
Data Warehouses
- Amazon Redshift
- Amazon Redshift Serverless
- Azure Synapse Analytics
- Databricks
- Firebolt
- Google BigQuery
- Hevo Managed Google BigQuery
- Snowflake
-
Destination FAQs
- Can I change the primary key in my Destination table?
- How do I change the data type of table columns?
- Can I change the Destination table name after creating the Pipeline?
- How can I change or delete the Destination table prefix?
- Why does my Destination have deleted Source records?
- How do I filter deleted Events from the Destination?
- Does a data load regenerate deleted Hevo metadata columns?
- How do I filter out specific fields before loading data?
- Transform
- Alerts
- Account Management
- Activate
- Glossary
Releases- Release 2.30 (Oct 21-Nov 18, 2024)
- Release 2.29 (Sep 30-Oct 22, 2024)
-
2024 Releases
- Release 2.28 (Sep 02-30, 2024)
- Release 2.27 (Aug 05-Sep 02, 2024)
- Release 2.26 (Jul 08-Aug 05, 2024)
- Release 2.25 (Jun 10-Jul 08, 2024)
- Release 2.24 (May 06-Jun 10, 2024)
- Release 2.23 (Apr 08-May 06, 2024)
- Release 2.22 (Mar 11-Apr 08, 2024)
- Release 2.21 (Feb 12-Mar 11, 2024)
- Release 2.20 (Jan 15-Feb 12, 2024)
-
2023 Releases
- Release 2.19 (Dec 04, 2023-Jan 15, 2024)
- Release Version 2.18
- Release Version 2.17
- Release Version 2.16 (with breaking changes)
- Release Version 2.15 (with breaking changes)
- Release Version 2.14
- Release Version 2.13
- Release Version 2.12
- Release Version 2.11
- Release Version 2.10
- Release Version 2.09
- Release Version 2.08
- Release Version 2.07
- Release Version 2.06
-
2022 Releases
- Release Version 2.05
- Release Version 2.04
- Release Version 2.03
- Release Version 2.02
- Release Version 2.01
- Release Version 2.00
- Release Version 1.99
- Release Version 1.98
- Release Version 1.97
- Release Version 1.96
- Release Version 1.95
- Release Version 1.93 & 1.94
- Release Version 1.92
- Release Version 1.91
- Release Version 1.90
- Release Version 1.89
- Release Version 1.88
- Release Version 1.87
- Release Version 1.86
- Release Version 1.84 & 1.85
- Release Version 1.83
- Release Version 1.82
- Release Version 1.81
- Release Version 1.80 (Jan-24-2022)
- Release Version 1.79 (Jan-03-2022)
-
2021 Releases
- Release Version 1.78 (Dec-20-2021)
- Release Version 1.77 (Dec-06-2021)
- Release Version 1.76 (Nov-22-2021)
- Release Version 1.75 (Nov-09-2021)
- Release Version 1.74 (Oct-25-2021)
- Release Version 1.73 (Oct-04-2021)
- Release Version 1.72 (Sep-20-2021)
- Release Version 1.71 (Sep-09-2021)
- Release Version 1.70 (Aug-23-2021)
- Release Version 1.69 (Aug-09-2021)
- Release Version 1.68 (Jul-26-2021)
- Release Version 1.67 (Jul-12-2021)
- Release Version 1.66 (Jun-28-2021)
- Release Version 1.65 (Jun-14-2021)
- Release Version 1.64 (Jun-01-2021)
- Release Version 1.63 (May-19-2021)
- Release Version 1.62 (May-05-2021)
- Release Version 1.61 (Apr-20-2021)
- Release Version 1.60 (Apr-06-2021)
- Release Version 1.59 (Mar-23-2021)
- Release Version 1.58 (Mar-09-2021)
- Release Version 1.57 (Feb-22-2021)
- Release Version 1.56 (Feb-09-2021)
- Release Version 1.55 (Jan-25-2021)
- Release Version 1.54 (Jan-12-2021)
-
2020 Releases
- Release Version 1.53 (Dec-22-2020)
- Release Version 1.52 (Dec-03-2020)
- Release Version 1.51 (Nov-10-2020)
- Release Version 1.50 (Oct-19-2020)
- Release Version 1.49 (Sep-28-2020)
- Release Version 1.48 (Sep-01-2020)
- Release Version 1.47 (Aug-06-2020)
- Release Version 1.46 (Jul-21-2020)
- Release Version 1.45 (Jul-02-2020)
- Release Version 1.44 (Jun-11-2020)
- Release Version 1.43 (May-15-2020)
- Release Version 1.42 (Apr-30-2020)
- Release Version 1.41 (Apr-2020)
- Release Version 1.40 (Mar-2020)
- Release Version 1.39 (Feb-2020)
- Release Version 1.38 (Jan-2020)
- Early Access New
- Upcoming Features
Google Cloud Storage (GCS)
Google Cloud Storage (GCS) is a storage platform that is fast, cost-effective, secure, and used for storing unstructured data (objects) in any file format in a bucket. You can use this data for multiple processes, such as creating a BigQuery data warehouse, and running analytical processes. Hevo supports replication of data from your GCS bucket in the following file formats: AVRO, CSV, JSON, and XML.
As of Release 1.66, Hevo adds the __hevo_source_modified_at
field to the Destination as a metadata field. For existing Pipelines that have this field:
-
If this field is displayed in the Schema Mapper, you must ignore it and not try to map it to a Destination table column, else the Pipeline displays an error.
-
Hevo automatically loads the information for the
__hevo_source_modified_at
column, which is already present in the Destination table.
You can, however, continue to use __hevo_source_modified_at
to create transformations using the function event.getSourceModifiedAt()
. Read Metadata Column __hevo_source_modified_at
.
Prerequisites
-
An active GCS account from which data is to be ingested exists.
-
The GCS bucket name is available to allow Hevo to ingest data from it.
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You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo, to create the Pipeline.
Obtaining the GCS Bucket Name and Folder Path
To obtain the GCS bucket name and folder path:
-
Log in to your Google Cloud console.
-
In the top navigation bar, click the Select a project button.
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In the Select a Resource window, search and select the project which contains your storage bucket. For example, Hevo Doc.
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In the left navigation menu, hover over Cloud Storage and click Buckets.
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On the Buckets page, copy the name of the bucket from which you want to ingest data. For example, hevo-sales-bucket as shown in the image below.
-
(Optional) Obtain the path to a specific folder or subfolder within a bucket if you want to ingest data only from that folder. To do so:
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Click the bucket which contains the folder or subfolder. For example, hevo-sales-bucket.
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On the Bucket details page, click the folder or subfolder from which you want to ingest data, and click the Copy icon to copy its path.
-
Use these details while creating your Hevo Pipeline.
Configuring Google Cloud Storage as a Source
To configure Google Cloud Storage as a Source in Hevo:
-
Click PIPELINES in the Navigation Bar.
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Click + CREATE PIPELINE in the Pipelines List View.
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On the Select Source Type page, select GCS.
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On the Configure your GCS account page, select the authentication method for connecting to your GCS Source:
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To connect with a User Account, do one of the following:
-
Select a previously configured account and click CONTINUE.
-
Click + ADD GCS ACCOUNT and perform the following steps to configure an account:
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Select your Google account that has access to the GCS bucket you intend to connect.
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Click Allow to authorize Hevo to read data from the bucket.
-
-
-
To connect with a Service Account, do one of the following:
Note: The service account must be granted the Storage Object Viewer role on the bucket from which you want to ingest data.
-
Select a previously configured account and click CONTINUE.
-
Click the attach () icon to upload the Service Account Key and click CONFIGURE GCS ACCOUNT.
Note: Hevo supports only JSON format for the service account key file.
-
-
-
On the Configure your GCS Source page, specify the following:
-
Pipeline Name: A unique name for your Pipeline, not exceeding 255 characters.
-
Bucket Name: The name of the bucket from which you want to ingest data.
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Path Prefix: The prefix of the path for the directory that contains your data. By default, Hevo ingests data from the root of the bucket. To ingest data only from a specific folder or subfolder within the bucket, specify the folder path that you obtained from your Google Cloud console in the following format: <folder name>/<subfolder name>/.
For example, if the path you obtained is hevo-sales-bucket/HevoSalesData/SalesReports, then specify HevoSalesData/SalesReports/.
-
File Format: The format of the data file in the Source. Hevo supports the AVRO, CSV, JSON, and XML file formats to ingest data.
Note: You can select only one file format at a time. If your Source data is in a different format, you can export the data to either of the supported formats, and then ingest the files.
Based on the format you select, you must specify some additional settings:
-
CSV:
-
Specify the Field Delimiter. This is the character on which fields in each line are separated. For example, `\t`, or `,`.
-
Disable the Treat First Row As Column Headers option if the Source data file does not contain column headers. Hevo, then, automatically creates these during ingestion. Default setting: Enabled. Refer to section, Example.
-
Enable the Create Event Types from folders option if the selected folder(s) have subfolders containing files in different formats. Hevo reads each subfolder as a separate Event Type and creates a separate table in the Destination for each of your selected folders.
Note: Files lying at the prefix path (and not in a subdirectory) are ignored.
-
-
JSON:
-
Enable the Create Event Types from folders option if the selected folder(s) have subfolders containing files in different formats. Hevo reads each subfolder as a separate Event Type and creates a separate table in the Destination for each of your selected folders.
Note: Files lying at the prefix path (and not in a subdirectory) are ignored.
-
-
XML:
-
Enable the Create Event Types from folders option if the selected folder(s) have subfolders containing files in different formats. Hevo reads each subfolder as a separate Event Type and creates a separate table in the Destination for each of your selected folders.
Note: Files lying at the prefix path (and not in a subdirectory) are ignored.
-
-
-
Include compressed files: Enable this option if you want to ingest compressed files of the selected file format from the folders. Hevo currently supports the tar.gz and zip compression types only. Hevo automatically unzips these compressed files on ingestion. Further, Hevo re-ingests these files if they are updated in your GCS account, as it is not possible to identify individual changes.
-
Convert date/time format fields to timestamp: Enable this option if you want to convert the date/time format within the files of selected folders to timestamp. For example, the date/time format 07/11/2022, 12:39:23 is converted to timestamp, 1667804963.
-
-
Click TEST & CONTINUE.
-
Proceed to configuring the data ingestion and setting up the Destination.
Data Replication
For Teams Created | Default Ingestion Frequency | Minimum Ingestion Frequency | Maximum Ingestion Frequency | Custom Frequency Range (in Hrs) |
---|---|---|---|---|
Before Release 2.21 | 5 Mins | 5 Mins | 3 Hrs | 1-3 |
After Release 2.21 | 6 Hrs | 30 Mins | 24 Hrs | 1-24 |
Note: The custom frequency must be set in hours as an integer value. For example, 1, 2, or 3 but not 1.5 or 1.75.
Additional Information
Read the detailed Hevo documentation for the following related topics:
Example: Automatic Column Header Creation for CSV Tables
Consider the following data in CSV format, which has no column headers.
CLAY COUNTY,32003,11973623
CLAY COUNTY,32003,46448094
CLAY COUNTY,32003,55206893
CLAY COUNTY,32003,15333743
SUWANNEE COUNTY,32060,85751490
SUWANNEE COUNTY,32062,50972562
ST JOHNS COUNTY,846636,32033,
NASSAU COUNTY,32025,88310177
NASSAU COUNTY,32041,34865452
If you disable the Treat first row as column headers option, Hevo auto-generates the column headers, as seen in the schema map below:
The record in the Destination appears as follows:
Limitations
-
Hevo does not consider the character used as a delimiter in CSV files as data. This is true even if you place an escape character (“\”) before the delimiter.
For example, suppose the delimiter for your CSV file is a “;”, and the data record in your GCS Source is “A\;B”. Hevo ingests this data as two separate fields, as it does not identify the semicolon as a part of the data.
See Also
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
May-27-2024 | 2.23.4 | Added information about connecting to GCS with service accounts in the Configuring Google Cloud Storage as a Source section. |
Mar-05-2024 | 2.21 | Updated the ingestion frequency table in the Data Replication section. |
Oct-30-2023 | NA | Added section, Obtaining the GCS Bucket Name and Folder Path. |
Jul-25-2023 | NA | Added limitation about Hevo not handling escape characters in CSV files. |
Jan-10-2023 | NA | Updated the page for consistent information structure. |
Dec-20-2022 | NA | Added section, Limitations. |
Nov-08-2022 | NA | Updated section, Configuring Google Cloud Storage as a Source to add information about the Convert date/time format fields to timestamp option. |
Sep-21-2022 | NA | Added a note in section, Configuring Google Cloud Storage as a Source. |
Mar-21-2022 | 1.85 | Removed section, Limitations as Hevo now supports UTF-16 encoding format for CSV files. |
Oct-25-2021 | NA | Added section, Data Replication. |
Jun-28-2021 | 1.66 | Updated the page overview with information about __hevo_source_modified_at being uploaded as a metadata field from Release 1.66 onwards. |
Feb-22-2021 | NA | Added the limitation about Hevo not supporting UTF-16 encoding format for CSV data. |