Data Pipeline
  • Data Pipeline
    • About Data Pipeline
    • Design Philosophy
    • Low Code Visual Authoring
    • Real-time and Batch Orchestration
    • Event based Process Orchestration
    • ML and Data Ops
    • Distributed Compute
    • Fault Tolerant and Auto-recovery
    • Extensibility via Custom Scripting
  • Getting Started
    • Homepage
      • List Pipelines
      • Creating a New Pipeline
        • Adding Components to Canvas
        • Connecting Components
          • Events [Kafka and Data Sync]
        • Memory and CPU Allocations
      • List Jobs
      • Create Job
        • Job Editor Page
        • Task Components
          • Readers
            • HDFS Reader
            • MongoDB Reader
            • DB Reader
            • S3 Reader
            • Azure Blob Reader
            • ES Reader
            • Sandbox Reader
          • Writers
            • HDFS Writer
            • Azure Writer
            • DB Writer
            • ES Writer
            • S3 Writer
            • Sandbox Writer
            • Mongodb Writer
            • Kafka Producer
          • Transformations
        • PySpark Job
        • Python Job
      • List Components
      • Delete Orphan Pods
      • Scheduler
      • Data Channel
      • Cluster Event
      • Trash
      • Settings
    • Pipeline Workflow Editor
      • Pipeline Toolbar
        • Pipeline Overview
        • Pipeline Testing
        • Search Component in Pipelines
        • Push Pipeline (to VCS/GIT)
        • Pull Pipeline
        • Full Screen
        • Log Panel
        • Event Panel
        • Activate/Deactivate Pipeline
        • Update Pipeline
        • Failure Analysis
        • Pipeline Monitoring
        • Delete Pipeline
      • Component Panel
      • Right-side Panel
    • Testing Suite
    • Activating Pipeline
    • Monitoring Pipeline
  • Components
    • Adding Components to Workflow
    • Component Architecture
    • Component Base Configuration
    • Resource Configuration
    • Intelligent Scaling
    • Connection Validation
    • Readers
      • S3 Reader
      • HDFS Reader
      • DB Reader
      • ES Reader
      • SFTP Stream Reader
      • SFTP Reader
      • Mongo DB Reader
        • MongoDB Reader Lite (PyMongo Reader)
        • MongoDB Reader
      • Azure Blob Reader
      • Azure Metadata Reader
      • ClickHouse Reader (Docker)
      • Sandbox Reader
      • Azure Blob Reader
    • Writers
      • S3 Writer
      • DB Writer
      • HDFS Writer
      • ES Writer
      • Video Writer
      • Azure Writer
      • ClickHouse Writer (Docker)
      • Sandbox Writer
      • MongoDB Writers
        • MongoDB Writer
        • MongoDB Writer Lite (PyMongo Writer)
    • Machine Learning
      • DSLab Runner
      • AutoML Runner
    • Consumers
      • SFTP Monitor
      • MQTT Consumer
      • Video Stream Consumer
      • Eventhub Subscriber
      • Twitter Scrapper
      • Mongo ChangeStream
      • Rabbit MQ Consumer
      • AWS SNS Monitor
      • Kafka Consumer
      • API Ingestion and Webhook Listener
    • Producers
      • WebSocket Producer
      • Eventhub Publisher
      • EventGrid Producer
      • RabbitMQ Producer
      • Kafka Producer
    • Transformations
      • SQL Component
      • Dateprep Script Runner
      • File Splitter
      • Rule Splitter
      • Stored Producer Runner
      • Flatten JSON
      • Email Component
      • Pandas Query Component
      • Enrichment Component
      • Mongo Aggregation
      • Data Loss Protection
      • Data Preparation (Docker)
      • Rest Api Component
      • Schema Validator
    • Scripting
      • Script Runner
      • Python Script
        • Keeping Different Versions of the Python Script in VCS
    • Scheduler
  • Custom Components
  • Advance Configuration & Monitoring
    • Configuration
      • Default Component Configuration
      • Logger
    • Data Channel
    • Cluster Events
    • System Component Status
  • Version Control
  • Use Cases
Powered by GitBook
On this page
  • Basic Information
  • Meta Information
  • Configuration fields when SNS Monitor is disabled
  • Configuration fields when SNS Monitor is enabled
  • Selected Columns
  • Partition Columns
  • Saving the Component Configuration
  1. Components
  2. Readers

S3 Reader

PreviousReadersNextHDFS Reader

Last updated 1 year ago

S3 Reader component typically authenticate with S3 using AWS credentials, such as an access key ID and secret access key, to gain access to the S3 bucket and its contents. S3 Reader is designed to read and access data stored in an S3 bucket in AWS.

All component configurations are classified broadly into the following sections:

  • Meta Information

  • ​

  • ​​

Check out the given demonstration to configure the S3 component and use it in a pipeline workflow.

  • Navigate to the Data Pipeline Editor.

  • Expand the Reader section provided under the Component Pallet.

  • Drag and drop the S3 Reader component to the Workflow Editor.

  • Click on the dragged S3 Reader to get the component properties tabs.

Basic Information

It is the default tab to open for the component while configuring it.

  • Invocation Type: Select an invocation mode out of ‘Real-Time’ or ‘Batch’ using the drop-down menu.

  • Deployment Type: It displays the deployment type for the reader component. This field comes pre-selected.

  • Container Image Version: It displays the image version for the docker container. This field comes pre-selected.

  • Failover Event: Select a failover Event from the drop-down menu.

  • Batch Size (min 10): Provide the maximum number of records to be processed in one execution cycle (Min limit for this field is 10).

Meta Information

Open the ‘Meta Information’ tab and fill in all the connection-specific details for the S3 Reader.·

Configuration fields when SNS Monitor is disabled

  • Bucket Name (*): Folder Name

  • Zone (*): S3 Zone location

  • Access Key (*): Access key shared by AWS to login

  • Secret Key (*): Secret key shared by AWS to login

  • Table (*): Mention the Table or object name which is to be read.

  • File Type (*): Select a file type from the drop-down menu (CSV, JSON, PARQUET, AVRO are the supported file types)

  • Limit: Set a limit for the number of records.

  • Query: Insert an SQL query.

Configuration fields when SNS Monitor is enabled

  • Access Key (*): Access key shared by AWS to login

  • Secret Key (*): Secret key shared by AWS to login

  • Table (*): Mention the Table or object name which has to be read

  • File Type (*): Select a file type from the drop-down menu (CSV, JSON, PARQUET, AVRO, XML are the supported file types)

  • Limit: Set limit for the number of records

  • Query: Insert a Spark SQL query (it supports query containing a join statement as well).

Selected Columns

There is also a section for the selected columns in the Meta Information tab if the user can select some specific columns from the table to read data instead of selecting a complete table so this can be achieved by using the ‘Selected Columns’ section. Select the columns which you want to read and if you want to change the name of the column, then put that name in the alias name section otherwise keep the alias name the same as of column name and then select a Column Type from the drop-down menu.

or

Use ‘Download Data’ and ‘Upload File’ options to select the desired columns.

Partition Columns

Provide a unique Key column name to partition data in Spark.​

Saving the Component Configuration

  • Click the Save Component in Storage icon after doing all the configurations to save the reader component.​

  • A notification message appears to inform about the component configuration success.

Please Note:

  • (*) the symbol indicates that the field is mandatory.

  • Either table or query must be specified for the data readers except for SFTP Reader.

  • Selected Columns- There should not be a data type mismatch in the Column Type for all the Reader components.

  • The Meta Information fields may vary based on the selected File Type.

    • All the possibilities are mentioned below:

      • CSV: ‘Header’ and ‘Infer Schema’ fields get displayed with CSV as the selected File Type. Enable Header option to get the Header of the reading file and enable Infer Schema option to get true schema of the column in the CSV file.

      • JSON: ‘Multiline’ and ‘Charset’ fields get displayed with JSON as the selected File Type. Check-in the Multiline option if there is any multiline string in the file.

      • PARQUET: No extra field gets displayed with PARQUET as the selected File Type.

      • AVRO: This File Type provides two drop-down menus.

        • Compression: Select an option out of the ‘Deflate’ and ‘Snappy’ options.

        • Compression Level: This field appears for the Deflate compression option. It provides 0 to 9 levels via a drop-down menu.​

      • XML: Select this option to read XML file. If this option is selected, the following fields will get displayed:

        • Infer schema: Enable this option to get true schema of the column.

        • Path: Provide the path of the file.

        • Root Tag: Provide the root tag from the XML files.

        • Row Tags: Provide the row tags from the XML files.

        • Join Row Tags: Enable this option to join multiple row tags.

​Basic Information​
Resource Configuration​
Connection Validation
How S3 Reader reads the data from the specified table name