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NEW QUESTION # 195
A data engineer is using the Snowflake Spark connector to write data to a Snowflake table. The write operation fails consistently with the error 'net.snowflake.client.jdbc.SnowflakeSQLException: SQL execution error: String '. ' is too long (maximum is 16777216)'. Which of the following is the most likely cause and how can it be resolved using Spark Connector?
Answer: E
Explanation:
The error message clearly states that a string is too long. While options A might seem plausible, it is better to pre-process data on spark using 0, 16777216))'. This helps to ensure data conforms to the desired constraints before reaching snowflake. Option B addresses performance, but is not a root cause of the error. Option C relates to nulls but the error message is for maximum string length.
NEW QUESTION # 196
You are tasked with sharing a subset of a customer table (CUSTOMER DATA') residing in your organization's Snowflake account with a partner organization. You need to mask personally identifiable information (PII) while providing near real-time updates. You decide to use a secure view. Which of the following SQL statements is the MOST efficient and secure way to accomplish this, assuming the partner only needs 'customer id', 'masked_email', 'city', and 'state'? The email should be masked using SHA256.
Answer: C
Explanation:
Option A correctly creates a SECURE VIEW, which is essential for data sharing as it prevents the partner from seeing the underlying table definition. It directly masks the email using SHA256. While Option C uses a hypothetical 'SYSTEM$MASK EMAIL' function, SHA256 is a readily available and standard masking method. Options B, D, and E do not create a secure view or properly grant access for data sharing. The correct method to share is to create secure view and then share using the share object.
NEW QUESTION # 197
A data provider wants to create a Listing in the Snowflake Marketplace. They want to ensure that consumers can only access the data in a secure and controlled manner. The provider needs to restrict data access based on specific roles within the consumer's Snowflake account and track data usage. Which of the following steps are NECESSARY to achieve these requirements?
Answer: D
Explanation:
Row-level security policies are critical for restricting data access based on consumer roles. Secure views can achieve similar outcomes, but row-level policies provides a more structured and scalable solution. Sharing the tables and views allows consumers to directly query the data, while the security policies enforce the access restrictions. Snowflake's account usage views provide the necessary tools for tracking data usage by consumers. Creating Reader accounts, and not using listings at all are valid approaches but don't make use of Snowflake Listings.
NEW QUESTION # 198
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'
Answer: D
Explanation:
The error message 'JSON document is not well formed: invalid character at position 12345' clearly indicates that the source data contains invalid JSON. While schema mismatch (C) and rate limiting (D) can cause data loading issues, the specific error message points directly to corrupted JSON data (B). Option A is incorrect because the STRIP OUTER ARRAY parameter is only relevant if the file contains an array and might not be the cause of JSON parsing errors. E is possible, but the error points to invalid JSON and not simply invalid data for a particular column.
NEW QUESTION # 199
You are ingesting data from an external stage (AWS S3) into a Snowflake table using Snowpipe. Data files are continuously being uploaded to the stage. After several hours, you notice that some data files are not being loaded. You check the Snowpipe error notifications and see 'net.snowflake.ingest.errors.FileSizeLimitExceededError'. You have already verified that the Snowpipe is correctly configured and the user has the necessary permissions. What are the MOST LIKELY reasons for this error and how can you resolve them?
Answer: A
Explanation:
The 'net.snowflake.ingest.errors.FileSizeLimitExceededError' clearly indicates that the size of the data files being ingested is exceeding the maximum allowed size for Snowpipe. While Snowflake does have storage capacity limits, that is not the root cause of this specific error. Splitting the files into smaller sizes prior to uploading will allow Snowpipe to process the data without exceeding the size limit. While network errors can occur, the error message is specific to file size. Snowpipe does not use 'MAX CONCURRENCY parameter. It automatically adjusts the concurrency The file format issues will create different error.
NEW QUESTION # 200
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