Connectors → Apache Hadoop
About Apache Hadoop
Apache Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware. It has many similarities with existing distributed file systems. However, the differences from other distributed file systems are significant. HDFS is highly fault-tolerant and is designed to be deployed on low-cost hardware. HDFS provides high throughput access to application data and is suitable for applications that have large data sets. With the Apache Hadoop Web UI, you can typically access browse the HDFS file system.
Apache Hadoop Connector
The Apache Hadoop Connector enables Incorta to access files stored in an HDFS directory. Incorta is able to load the following file types from HDFS:
- Text (csv, tsv, tab, txt)
- Excel (xlsx)
- Parquet
- Optimized Row Columnar (ORC)
The Apache Hadoop connector supports the following Incorta specific functionality:
Feature | Supported |
---|---|
Chunking | ✔ |
Data Agent | |
Encryption at Ingest | |
Incremental Load | ✔ |
Multi-Source | ✔ |
OAuth | |
Performance Optimized | ✔ |
Remote | ✔ |
Single-Source | ✔ |
Spark Extraction | |
Webhook Callbacks | ✔ |
Steps to connect Apache Hadoop and Incorta
To connect Apache Hadoop and Incorta, here are the high level steps, tools, and procedures:
- Create an external data source
- Create a schema with the Schema Wizard
- or, Create a schema with the Schema Designer
- Load the schema
- Explore the schema
Create an external data source
Here are the steps to create a external data source with the Apache Hadoop connector:
- Sign in to the Incorta Direct Data Platform.
- In the Navigation bar, select Data.
- In the Action bar, select + New → Add Data Source.
- In the Choose a Data Source dialog, in Data lake, select Data Lake - HDFS.
- In the New Data Source dialog, specify the applicable connector properties.
- To test, select Test Connection.
- Select Ok to save your changes.
Apache Hadoop connector properties
Here are the properties for the Apache Hadoop connector:
Property | Control | Description |
---|---|---|
Data Source Name | text box | Enter the name of the data source |
Directory | text box | Enter the path to the public HDFS user directory using a hdfs URL such as: hdfs://<PUBLIC_IP>:<PORT>/user/<USER_NAME_OR_PATH> Replace <PUBLIC_IP> with a the HDFS website public IP address or public DNS.The default <PORT> is 50700. <USER_NAME_OR_PATH> represents the user and/or path to the HDFS directory. |
Create a schema with the Schema Wizard
Here are the steps to create an Apache Hadoop schema with the Schema Wizard:
- Sign in to the Incorta Direct Data Platform.
- In the Navigation bar, select Schema.
- In the Action bar, select + New → Schema Wizard
- In (1) Choose a Source, specify the following:
- For Enter a name, enter the schema name.
- For Select a Datasource, select the Apache Hadoop external data source.
- Optionally create a description.
- In the Schema Wizard footer, select Next.
- In (2) Manage Tables, in the Data Panel, navigate the directory tree as necessary to select the Apache Hadoop files. You can either check the Select All checkbox or select individual sheets.
- In the Schema Wizard footer, select Next.
- In (3) Finalize, in the Schema Wizard footer, select Create Schema.
Create a schema with the Schema Designer
Here are the steps to create an Apache Hadoop schema using the [Schema Designer]:
- Sign in to the Incorta Direct Data Platform.
- In the Navigation bar, select Schema.
- In the Action bar, select + New → Create Schema.
- In Name, specify the schema name, and select Save.
- In Start adding tables to your schema, select Data Lake.
- In the Data Source dialog, specify the Apache Hadoop table data source properties.
- Select Add.
- In the Table Editor, in the Table Summary section, enter the table name.
- To save your changes, select Done in the Action bar.
Apache Hadoop table data source properties
For a schema table in Incorta, you can define the following Apache Hadoop specific data source properties as follows:
Property | Control | Description |
---|---|---|
Type | drop down list | Default is Data Lake |
Data Source | drop down list | Select the Apache Hadoop external data source |
Remote | toggle | Enable this option to remotely access file data, which means no data is loaded to Incorta. See the Summary of Data Access Methods table for details on how setting this and the Performance Optimized property affects data accessibility. |
File Type | drop down list | Select a file type option: ● Text (csv, tsv, tab, txt) ● Excel (xlsx) - not an option with Remote enabled ● Parquet ● ORC |
Incremental | toggle | Enables incremental loading for the schema table |
Has Header? | toggle | This property appears when Remote is disabled and the File Type is Text. Enable this property to indicate the data source has a header row. |
Rows to Skip | text box | This property appears when Remote is disabled and the File Type is Text. Enter the number of rows to skip from the top of the file. |
Wildcard Union | toggle | Enable this property to get incremental data file updates from an existing directory |
File Path | text box | This property appears when Wildcard Union is disabled. Enter the path to the data file, relative to the root directory configured in the data source. |
Worksheet | text box | This property appears when Wildcard Union is disabled and the File Type is Excel. Select the data file worksheet of interest. |
Update File | text box | This property appears when Incremental is enabled and Wildcard Union is disabled. Enter the path to the update file, relative to the root directory configured in the data source. |
Update Worksheet | text box | This property appears when the File Type is Excel, Incremental is enabled, and Wildcard Union is disabled. Select the update file worksheet of interest. |
Incremental Extract Using | drop down list | This property appears when Incremental and Wildcard Union are enabled. Select an incremental load method. |
Timestamp format in file name | drop down list | This property appears when the Timestamp in File Name option is selected for the Incremental Extract Using property. Select the timestamp format that appears in the file name. |
Directory Path | text box | This property appears when Wildcard Union is enabled. Enter the path to the directory, relative to the root directory configured in the data source. To use the root directory, enter ./ or . |
Apply Include Pattern on | drop down list | This property appears when Wildcard Union is enabled. Select either: ● File Name - apply pattern on all file names in the selected directory path ● File Relative Path - apply pattern on relative path in the selected directory path |
Include | text box | This property appears when Wildcard Union is enabled. This property appears when Wildcard Union is enabled. To include only certain files in the load process, enter a prefix to compare against: ● The names of the files in a directory if Apply Include Pattern on has a value of File Name. For example, entering sales* .parquet will load only those files that start with the word sales and end with .parquet .● The relative path in a directory if Apply Include Pattern has a value of File Relative Path. For example, entering sales will load those files in the sales directory. |
Exclude | text box | This property appears when Wildcard Union is enabled. To exclude files from the load process, enter a prefix to compare against. Files that match the prefix will not be loaded. |
Include Sub-Directories | toggle | This property appears when Wildcard Union is enabled. Enable this property to load files within all subdirectories of the directory path hierarchy. If an Include prefix is specified, only files or relative paths in the subdirectories matching the prefix will be loaded. |
Include Filename as a Column | toggle | This property appears when Wildcard Union is enabled. Enable this property to add the file name as the first column in the schema table. |
Date Format | drop down list | This property appears when the File Type is Text<. Select the text file date format. |
Timestamp Format | drop down list | This property appears when the File Type is Text. Select the text file timestamp format. |
Character Set | drop down list | This property appears when the File Type is Text. Select the text file character set. |
Separator | drop down list | This property appears when the File Type is Text. Select the text file separator. |
Enable Chunking | toggle | This property appears when the File Type is Text. Turn this property on to process the text file in chunks. |
Callback | toggle | Enable this property on to expose the Callback URL field |
Callback URL | text box | This property appears when the Callback toggle is enabled. Specify the URL. |
Summary of Data Access Methods Based on Remote and Performance Optimized Settings
Table Properties | Data Source Properties | Parquet | DDM | Memory | SQLi | MV/ Notebooks | Analytics |
---|---|---|---|---|---|---|---|
Performance Optimized = Off | Remote = On | No | No | No | Yes | Yes | No |
Performance Optimized = Off | Remote = Off | Yes | Yes | No | Yes | Yes | No, unless populated via MV/Notebook |
Performance Optimized = On | Remote = Off | Yes | Yes | Yes | Yes | Yes | Yes |
Incremental Extract Methods
Last Successful Extract Time: This option will load data from the time the last successful extract occurred.
Here is an example use case of Last Successful Extract Time:
- A directory containing all the sales data is located at
/path/to/sales
- The directory contains the following files:
/path/to/sales/sales_california.parquet
,/path/to/sales/sales_newyork.parquet
,/path/to/sales/illinois.parquet
When you perform a full load, the union of all existing files will be extracted into the same table. After that, if the directory receives a new file, such as /path/to/sales/sales_ohio.parquet, the next incremental load will pick up this file since its last modified timestamp will be more recent than that of the files extracted in the previous full load.
- A directory containing all the sales data is located at
Timestamp in File Name: This option will load data from the time specified in the file name.
Here is an example use case of Timestamp in File Name:
- A directory containing all the sales data is located at
/path/to/sales
- The directory receives a new file on daily basis:
/path/to/sales/sales_2020-04-01.parquet
,/path/to/sales/sales_2020-04-02.parquet
,/path/to/sales/sales_2020-04-03.parquet
When you perform a full load, the union of all existing files will be extracted into the same table. After that, if the directory receives a new file, such as
/path/to/sales/sales_2020-04-04.parquet
, the next incremental load will pick up this file since the timestamp in the file name is more recent than that of the files extracted in the previous full load.- A directory containing all the sales data is located at
Timestamp Formats in File Name
- yyyy-MM-dd
- dd.MM.yyyy
- dd-MMM-yy
- dd-MMM-yyyy
- yyyy-MM-dd HH.mm.ss
- Unix Epoch (seconds)
- Unix Epoch (milliseconds)
Text File Date Format
- yyyy-MM-dd
- dd/MM/yyyy
- dd.MM.yyyy
- dd/MMM/yyyy
- dd-MMM-yy
- dd-MMM-yyyy
- MM/dd/yyyy
- yyyy/MM/dd
- Unix Epoch (seconds
- Unix Epoch (milliseconds)
- Other
Text File Timestamp Format
- yyyy-MM-dd HH:mm:ss
- yyyy-MM-dd HH.mm.ss
- yyyy-MM-dd HH:mm:ss.SSS
- dd/MM/yyyy HH:mm:ss
- dd/MM/yyyy HH.mm.ss
- dd/MM/yyyy HH:mm:ss.SSS
- Unix Epoch (seconds
- Unix Epoch (milliseconds)
- Other
Text File Character Set
- US-ASCII
- ISO-8859-1
- UTF-8
- UTF-16BE
- UTF-16LE
- UTF-16
Text File Separator
- Comma
- Tab
- Other
View the schema diagram with the Schema Diagram Viewer
Here are the steps to view the schema diagram using the Schema Diagram Viewer:
- Sign in to the Incorta Direct Data Platform.
- In the Navigation bar, select Schema.
- In the list of schemas, select the Apache Hadoop schema.
- In the Schema Designer, in the Action bar, select Diagram.
Load the schema
Here are the steps to perform a Full Load of the Apache Hadoop schema using the Schema Designer:
- Sign in to the Incorta Direct Data Platform.
- In the Navigation bar, select Schema.
- In the list of schemas, select the Apache Hadoop schema.
- In the Schema Designer, in the Action bar, select Load → Load Now → Full.
- To review the load status, in Last Load Status, select the date.
Explore the schema
With the full load of the Apache Hadoop schema complete, you can use the Analyzer to explore the schema, create your first insight, and save the insight to a new dashboard.
To open the Analyzer from the schema, follow these steps:
- In the Navigation bar, select Schema.
- In the Schema Manager, in the List view, select the Apache Hadoop schema.
- In the Schema Designer, in the Action bar, select Explore Data.