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A data engineer needs to register a table named `orders` from an external CSV source where fields are pipe-delimited (`|`) and the first row contains the column headers. Which of the following Spark SQL DDL statements correctly creates this table?

Real Exam

Last updated: December 30, 2025 at 14:04

CREATE TABLE orders_csv(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)USING CSV
TABLEPROPERTIES (
  header = “false“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

CREATE TABLE orders_csv(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)USING CSV
TABLEPROPERTIES (
  header = “false“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

6.9%

CREATE TABLE orders_csv(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)STORED AS CSV
PROPERTIES (
  header = “true“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

CREATE TABLE orders_csv(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)STORED AS CSV
PROPERTIES (
  header = “true“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

Comments

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CREATE CSV TABLE orders_csv (
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)
OPTIONS (
  header = “false“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

CREATE CSV TABLE orders_csv (
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)
OPTIONS (
  header = “false“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

2.0%

CREATE TABLE orders_csv USING CSV(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)
OPTIONS (
  header = “true“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

CREATE TABLE orders_csv USING CSV(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)
OPTIONS (
  header = “true“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

10.8%

CREATE TABLE orders_csv(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)USING CSV
OPTIONS (
  header = “true“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

CREATE TABLE orders_csv(
  order_id LONG,
  order_customer_id INTEGER,
  order_timestamp TIMESTAMP,
  total_item_quantity INTEGER,
  order_amount DOUBLE,
  order_status STRING
)USING CSV
OPTIONS (
  header = “true“,
  delimiter = “|“
)
LOCATION “dbfs:/user/username/retail/orders-csv“

75.9%

Databricks Certified Data Engineer - Associate

Get started today

A data engineer needs to register a table named orders from an external CSV source where fields are pipe-delimited (|) and the first row contains the column headers. Which of the following Spark SQL DDL statements correctly creates this table?

Comments

A data engineer needs to register a table named `orders` from an external CSV source where fields are pipe-delimited (`|`) and the first row contains the column headers. Which of the following Spark SQL DDL statements correctly creates this table?