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You are using Snowpipe to continuously load JSON data from an Azure Blob Storage container into a Snowflake table. The data contains nested JSON structures. You observe that some records are not being loaded into the table, and the 'VALIDATION MODE shows 'PARSE ERROR' for these records. Examine the following COPY INTO statement and the relevant error message from 'VALIDATION MODE', and identify the most likely cause of the problem. COPY INTO my_table FROM FILE FORMAT = (TYPE = JSON STRIP OUTER ARRAY = TRUE) ON ERROR = CONTINUE; Error Message (from VALIDATION MODE): 'JSON document is not well formed: invalid character at position 12345'

• A. The JSON data contains invalid characters or formatting errors at position 12345, as indicated in the error message. Cleanse the source data to ensure it is well-formed JSON before loading.
• B. The Snowflake table schema does not match the structure of the JSON data. Verify that the column names and data types in the table are compatible with the JSON fields.
• C. The file format definition is missing a 'NULL IF' parameter which is causing Snowflake to attempt to load string values that should be NULL.
• D. Snowpipe is encountering rate limiting issues with Azure Blob Storage. Implement retry logic in your Snowpipe configuration.
• E. The 'STRIP OUTER ARRAY' parameter is causing the issue because the incoming JSON data is not wrapped in an array. Remove the 'STRIP OUTER ARRAY' parameter from the COPY INTO statement.

You have configured a Kafka Connector to load JSON data into a Snowflake table named 'ORDERS. The JSON data contains nested structures. However, Snowflake is only receiving the top- level fields, and the nested fields are being ignored. Which configuration option within the Kafka Connector needs to be adjusted to correctly flatten and load the nested JSON data into Snowflake?

• A. Enable the 'snowflake.ingest.stage' property and set it to a Snowflake internal stage.
• B. Use the 'transforms' configuration with the 'org.apache.kafka.connect.transforms.ExtractField$Value' transformation to extract specific fields.
• C. Configure the 'snowflake.data.field.name' property to specify the column in the Snowflake table where the entire JSON should be loaded as a VARIANT.
• D. Set the 'value.converter.schemas.enable' property to 'true'.
• E. Apply the 'org.apache.kafka.connect.transforms.Flatten' transformation to the 'transforms' configuration.

A data engineering team has created a Snowflake Listing to share their company's sales data'. They want to allow consumers to access the Listing programmatically. The consumers need to know when new versions of the Listing are available. What is the MOST efficient method for consumers to be notified about new Listing versions without continuously polling Snowflake?

• A. The data consumer implements a custom webhook endpoint that the data provider calls whenever a new Listing version is published. The data provider will need to maintain a list of all consumers.
• B. Snowflake automatically notifies consumers via an event notification service (e.g., AWS SNS, Azure Event Grid) integrated with the Data Marketplace when a new version is available.
• C. The data provider manually sends email notifications to each consumer whenever a new version is created.
• D. The consumer sets up a scheduled task in Snowflake to periodically query the 'SHOW VERSIONS command for the Listing.

Given the following scenario: You have an external table 'EXT SALES in Snowflake pointing to a data lake in Azure Blob Storage. The storage account network rules are configured to only allow specific IP addresses and virtual network subnets, enhancing security. You are getting intermittent errors when querying 'EXT SALES. Which of the following could be the cause(s) and the corresponding solution(s)? Select all that apply.

• A. The Snowflake IP addresses used to access the Azure Blob Storage are not whitelisted in the storage account's firewall settings. Solution: Obtain the Snowflake IP address ranges for your region and add them to the storage account's allowed IP addresses.
• B. The network connectivity between Snowflake and Azure Blob Storage is unstable. Solution: Implement retry logic in your queries to handle transient network errors.
• C. The Snowflake service principal does not have the correct permissions on the Azure Blob Storage account. Solution: Ensure the Snowflake service principal has the 'Storage Blob Data Reader' role assigned to it.
• D. The file format specified in the external table definition does not match the actual format of the files in Azure Blob Storage. Solution: Update the 'FILE_FORMAT parameter in the external table definition to match the correct file format.
• E. The table function cache is stale, causing access to non-existent files. Solution: Run 'ALTER EXTERNAL TABLE EXT_SALES REFRESH'.

You are building a data pipeline to ingest clickstream data into Snowflake. The raw data is landed in a stage and you are using a Stream on this stage to track new files. The data is then transformed and loaded into a target table 'CLICKSTREAM DATA. However, you notice that sometimes the same files are being processed multiple times, leading to duplicate records in 'CLICKSTREAM DATA. You are using the 'SYSTEM$STREAM HAS DATA' function to check if the stream has data before processing. What are the possible reasons this might be happening, and how can you prevent it? (Select all that apply)

• A. The transformation process is not idempotent. Even with the same input files, it produces different outputs each time it runs.
• B. The auto-ingest notification integration is configured incorrectly, causing duplicate notifications to be sent for the same files. This is particularly applicable when using cloud storage event triggers.
• C. The 'SYSTEM$STREAM HAS DATA' function is unreliable and should not be used for production data pipelines. Use 'COUNT( on the stream instead.
• D. The stream offset is not being advanced correctly after processing the files. Ensure that the files are consumed completely and a DML operation is performed to acknowledge consumption.
• E. The COPY INTO command used to load the files into Snowflake has the 'ON ERROR = CONTINUE option set, allowing it to skip corrupted files, causing subsequent processing to pick them up again.