Tecton

batch_cluster_config now available, Resolved Plan Hooks issue for Windows environments, Adds .tectonignore to ignore paths and files

  • Tony Chu
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Published: October 1, 2021
Last updated: December 1, 2021
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batch_cluster_config now available for Feature Table declarations

You can now include batch_cluster_config configuration in Feature Table declarations. By specifying an EMRClusterConfig or DatabricksClusterConfig configuration or referencing an ExistingClusterConfig, the ingest materialization jobs will run on a cluster of workers with the specified configuration options like instance type, instance size, and spark configurations.

FeatureTable(
    name="user_page_click_feature_table",
    entities=[content],
    schema=schema,
    online=True,
    offline=True,
    owner="example@tecton.ai",
    batch_cluster_config=DatabricksClusterConfig(
        instance_type="m5.2xlarge",
        number_of_workers=2,
        spark_config={
            "spark.executor.memory": "7000m",
        },
    ),
)

Resolved Plan Hooks issue for Windows environments

Previously including a plan.py would cause problems for users in a Windows environment. This issue is resolved in SDK version 0.0.54.

Adds .tectonignore to ignore paths and files

You can now add .tectonignore to your feature repository to ignore specified paths and files, similar to .gitignore. See the usage guide for an example.

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Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

CTA link

or

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Request a free trial

Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

CTA link

or

CTA button