We use the CAST() function to show the timestamp as a human-readable time and date.
SELECT
rating,
CAST(timeRecorded as timestamp)
FROM
movieRatings;
We use the CAST() function to show the timestamp as a human-readable time and date.
SELECT
rating,
CAST(timeRecorded as timestamp)
FROM
movieRatings;
DROP TABLE IF EXISTS movieRatings;
CREATE TABLE movieRatings (
userId INT,
movieId INT,
rating FLOAT,
timeRecorded INT
) USING csv OPTIONS (
PATH “/mnt/training/movies/20m/ratings.csv”,
header “true”
);
SELECT firstName
FROM PeopleDistinctNames
JOIN SSADistinctNames ON firstName = ssaFirstName
SELECT count(DISTINCT firstName)
FROM SSANames;
CREATE OR REPLACE TEMPORARY VIEW PeopleSavings AS
SELECT
firstName,
lastName,
year(birthDate) as birthYear,
salary,
salary * 0.2 AS savings
FROM
People10M;
park SQL is a component of Apache Spark that enables querying structured data using SQL syntax, either through SQL queries or DataFrame APIs. Here’s a brief overview of some basic queries you can perform using Spark SQL:
SELECT col1, col2 FROM table_name;SELECT * FROM table_name WHERE condition;SELECT COUNT(*), AVG(salary) FROM employee_table;SELECT department, AVG(salary) FROM employee_table GROUP BY department;SELECT * FROM table1 JOIN table2 ON table1.key = table2.key;SELECT * FROM table_name ORDER BY column_name ASC/DESC;SELECT * FROM table1 WHERE col1 IN (SELECT col2 FROM table2);ELECT department, employee_id, salary, AVG(salary) OVER (PARTITION BY department) AS avg_salary_department FROM employee_table;WITH cte AS ( SELECT department, AVG(salary) AS avg_salary FROM employee_table GROUP BY department ) SELECT * FROM cte WHERE avg_salary > 50000;SELECT col1 FROM table1 UNION SELECT col2 FROM table2;These are some of the basic SQL queries you can perform using Spark SQL. Keep in mind that Spark SQL supports a wide range of SQL functionalities, and you can use it to handle complex data manipulation and analysis tasks.
DROP TABLE IF EXISTS People10M;
CREATE TABLE People10M
USING parquet
OPTIONS (
path “/mnt/training/dataframes/people-10m.parquet”,
header “true”);
PI gateways play a crucial role in managing, securing, and optimizing communication between different microservices or between clients and servers. Here’s a list of both commercial and open-source API gateways:
It’s important to evaluate the specific requirements, features, and licensing considerations when choosing between commercial and open-source API gateways. The choice may depend on factors such as scalability, support, ease of integration, and available features.
Remember to check the official Flask documentation for the most up-to-date and accurate information. Additionally, exploring community forums, such as the Flask community on Stack Overflow, can be helpful for getting answers to specific questions.
Remember that the Rust ecosystem is dynamic, and new resources may become available. Always check the official Rust website and community channels for the latest information and updates.