AzureQueue Table Engine
This engine provides an integration with Azure Blob Storage ecosystem, allowing streaming data import.
Create Table
CREATE TABLE test (name String, value UInt32)
ENGINE = AzureQueue(...)
[SETTINGS]
[mode = '',]
[after_processing = 'keep',]
[keeper_path = '',]
...
Engine parameters
AzureQueue
parameters are the same as AzureBlobStorage
table engine supports. See parameters section here.
Example
CREATE TABLE azure_queue_engine_table (name String, value UInt32)
ENGINE=AzureQueue('DefaultEndpointsProtocol=http;AccountName=devstoreaccount1;AccountKey=Eby8vdM02xNOcqFlqUwJPLlmEtlCDXJ1OUzFT50uSRZ6IFsuFq2UVErCz4I6tq/K1SZFPTOtr/KBHBeksoGMGw==;BlobEndpoint=http://azurite1:10000/devstoreaccount1/data/')
SETTINGS
mode = 'unordered'
Settings
The set of supported settings is the same as for S3Queue
table engine, but without s3queue_
prefix. See full list of settings settings.
Description
SELECT
is not particularly useful for streaming import (except for debugging), because each file can be imported only once. It is more practical to create real-time threads using materialized views. To do this:
- Use the engine to create a table for consuming from specified path in S3 and consider it a data stream.
- Create a table with the desired structure.
- Create a materialized view that converts data from the engine and puts it into a previously created table.
When the MATERIALIZED VIEW
joins the engine, it starts collecting data in the background.
Example:
CREATE TABLE azure_queue_engine_table (name String, value UInt32)
ENGINE=AzureQueue('<endpoint>', 'CSV', 'gzip')
SETTINGS
mode = 'unordered';
CREATE TABLE stats (name String, value UInt32)
ENGINE = MergeTree() ORDER BY name;
CREATE MATERIALIZED VIEW consumer TO stats
AS SELECT name, value FROM azure_queue_engine_table;
SELECT * FROM stats ORDER BY name;
Virtual columns
_path
— Path to the file._file
— Name of the file.
For more information about virtual columns see here.