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Kusto Ingest Client

Project description

from azure.kusto.data import KustoConnectionStringBuilder, DataFormat
from azure.kusto.ingest import QueuedIngestClient, IngestionProperties, FileDescriptor, BlobDescriptor

ingestion_props = IngestionProperties(database="{database_name}", table="{table_name}", data_format=DataFormat.CSV)
client = QueuedIngestClient(KustoConnectionStringBuilder.with_interactive_login("https://ingest-{cluster_name}.kusto.windows.net"))

file_descriptor = FileDescriptor("{filename}.csv", 15360)  # in this example, the raw (uncompressed) size of the data is 15KB (15360 bytes)
client.ingest_from_file(file_descriptor, ingestion_properties=ingestion_props)
client.ingest_from_file("{filename}.csv", ingestion_properties=ingestion_props)

blob_descriptor = BlobDescriptor("https://{path_to_blob}.csv.gz?sas", 51200)  # in this example, the raw (uncompressed) size of the data is 50KB (52100 bytes)
client.ingest_from_blob(blob_descriptor, ingestion_properties=ingestion_props)

Overview

Kusto Python Ingest Client Library provides the capability to ingest data into Kusto clusters using Python. It is Python 3.x compatible and supports data types through familiar Python DB API interface.

It’s possible to use the library, for instance, from Jupyter Notebooks which are attached to Spark clusters, including, but not exclusively, Azure Databricks instances.

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