Get Data - SQL Database (Health)
SQL database is a relational database, managed using SQL programming language. A
health data set on a PostresSQL database has records of air quality, traffic congestion, car and bike accidents for a day in New York.
A password to access the PostgresSQL database is required before deploying.
No kdb+ knowledge required
No prior experience with q/kdb+ is required to build this pipeline. Replace the PostgreSQL connection details with any other to gain similar results.
health data using a local PostgreSQL client install
$ psql "sslmode=disable dbname=postgres user=postgres hostaddr=126.96.36.199" Password for user postgres: dxrHvgtjHHvsOH7B psql (14.1, server 13.4) Type "help" for help. postgres=> \connect health psql (14.1, server 13.4) You are now connected to database "health" as user "postgres". health=> \dt List of relations schema | name | type | owner -------+----------------------+-------+---------- public | health | table | postgres (5 rows)
1. Create and deploy a database
A database stores data on kdb Insights Enterprise. Available databases are listed under Assemblies of the Overview home page. If not available, create a database,
insights-demo, to store your data. .
To use a pipeline, your database must be deployed and active.
2. Import Data
Open the import wizard by clicking [+] in the ribbon menu or from the left-hand icon menu or Overview page. Then click Start Import to begin the process of building a pipeline; a pipeline is a connection of nodes to read data from source, transform to a kdb+ compatible format, then write to a kdb Insights Enterprise database.
Click Start Import to begin the data import process.
I want to learn more about the import wizard.
3. Select a Reader
A reader stores details of data to import. Select
PostgreSQL Relational database, and enter the details of the PostgresSQL database; required properties are marked with an
Select PosgresSQL from the relational database import options.
PostgresSQL database hosting
|Query*||select * from health|
Click Next when done.
I want to learn more about reader nodes.
4. Add a Schema
The schema is responsible for converting data to a type compatible with a kdb+ database. Every data table imported requires a schema; and every data table must have a
timestamp key to be compatible with kdb's time series columnar database.
insights-demo has a predefined schema for the
health data set.
|Apply a Schema||
To attach the schema to the data set:
insights-demoschema from the dropdown
Load schemas from the
healthtable from the
healthschema; Parse Strings is set as
autofor all fields.
Determines the requirement to parse input string data to other datatypes. Generally, parse strings is enabled for all
string fields unless your input is IPC or RT; retain the
Auto default if unsure.
Click Next when done.
I want to learn more about transform nodes.
5. Configure the Writer
Write transformed data to kdb Insights Enterprise database.
|Write Direct to HDB||No|
Click to review the pipeline in the pipeline viewer.
A pipeline created by the import wizard, reads data from its source, transforms to a kdb+ compatible format, and writes it to a kdb Insights Enterprise database.
Writer - kdb Insights Database node is essential for exploring data in a pipeline. The node defines the database to write too that must be active to receive data. Stream data uses its own writer node,
Writer - kdb Insights Stream.
I want to learn more about writer nodes.
6. Review the Pipeline
The pipeline is a linked set of nodes derived from each step of the import process.
The completed PostgresSQL pipeline.
7. Save the Pipeline
Save the pipeline as
Save the pipeline as
health-1 is listed under Pipelines in the left-hand menu.
8. Deploy the Pipeline
Deploy a pipeline to access it's data.
Deploy the pipeline.
Deploying a PostgresSQL pipeline requires a password to access the database:
Enter a password to access the PostgresSQL database.
Check the progress of pipeline under Running Pipelines of the Overview panel. The data is ready to query when
health pipeline available for querying.
I want to learn more about pipelines
9. Query the Datax
Query data on a successful deploy to the database.
10. Visualize the Data
Build a visualization from the data.