A. mask(email, ' ? ' )

B. hash(email)

C. sha1(email)

D. sha2(email, 0)

A. databricks clusters create 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster-name DataEngineer_cluster

B. databricks clusters add 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster-name Data Engineer_cluster

C. databricks compute add 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster-name Data Engineer_cluster

D. databricks compute create 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster-name Data Engineer_cluster

A. 정규 표현식

B. 줄리아

C. pyspsark.ml.feature

D. Scala 데이터셋

E. C++

A. SELECT percent_null
FROM prod_catalog.prod_schema.customer_data_profile_metrics
WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 1 ' DAY
Alert Condition: percent_null > 5
Notification Frequency: At most every 24 hours

B. WITH daily_avg AS (
SELECT DATE_TRUNC( ' DAY ' , window.end) AS day,
AVG(percent_null) AS avg_null
FROM prod_catalog.prod_schema.customer_data_profile_metrics
GROUP BY DATE_TRUNC( ' DAY ' , window.end)
)
SELECT day, avg_null
FROM daily_avg
ORDER BY day DESC
LIMIT 3
Alert Condition: ALL avg_null > 5 for the latest 3 rows
Notification Frequency: Just once

C. SELECT AVG(percent_null) AS daily_avg
FROM prod_catalog.prod_schema.customer_data_profile_metrics
WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 3 ' DAY
Alert Condition: daily_avg > 5
Notification Frequency: Each time alert is evaluated

D. SELECT SUM(CASE WHEN percent_null > 5 THEN 1 ELSE 0 END) AS violation_days FROM prod_catalog.prod_schema.customer_data_profile_metrics WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 3 ' DAY Alert Condition: violation_days > = 3 Notification Frequency: Just once

A. 실행기 상세 화면 및 실행기 로그 파일

B. 스테이지 상세 화면 및 쿼리 상세 화면

C. 스테이지 상세 화면 및 실행자 파일

D. 드라이버 및 실행기 로그 파일