One of the most common causes of negative float is the introduction of constraints in the schedule that can't be met. Consider a project schedule where each of the first three activities has some total float because a constraint is placed on the third activity. The float exists because the ...
The float represents the net effect of checks in the process of clearing. A common measure of a float is theaverage daily float, calculated by dividing the total value of checks in the collection process during a specified period by the number of days in the period. The total value of che...
The generated sql is as followsCREATE TABLE testSummerboot.`Customer` ( `Name` text NULL, `Age` float NOT NULL, `CustomerNo` text NULL, `TotalConsumptionAmount` decimal(18,2) NOT NULL, `Id` int NOT NULL AUTO_INCREMENT, `LastUpdateOn` datetime NULL, `LastUpdateBy` text NULL, `Create...
Learn about common data types—booleans, integers, strings, and more—and their importance in the context of gathering data.
Here's a fun project attempting to explain what exactly is happening under the hood for some counter-intuitive snippets and lesser-known features in Python.While some of the examples you see below may not be WTFs in the truest sense, but they'll reveal some of the interesting parts of ...
Beginning with MySQL 8.4.0, the deprecated mysql_native_password authentication plugin is no longer enabled by default. To enable it, start the server with --mysql-native-password=ON (added in MySQL 8.4.0), or by including mysql_native_password=ON in the [mysqld] section of your MySQL co...
Forum Discussion Gaz_Thornton As for the formula style, better is to use spaces and/or multiline to avoid extra errors with formula parts =IF(E5>80,0,CEILING.MATH(E5,10))=IF(E5>80,0,CEILING.MATH(E5,10))=IF(E5>80,0,CEILING.MATH(E5,10))...
Here is how the NTLM flow works: A user accesses a client computer and provides a domain name, user name, and a password. The client computes a cryptographic hash of the password and discards the actual password. The client sends the user name to the server (in plaintext). ...
df.createOrReplaceTempView("Pizza") sql_results = spark.sql("SELECT sum(price.float64),count(*) FROM Pizza where timestamp.string is not null and item.string = 'Pizza'") sql_results.show() Using full fidelity schema with SQL You can use the following syntax example, with the same docu...
df.createOrReplaceTempView("Pizza") sql_results = spark.sql("SELECT sum(price.float64),count(*) FROM Pizza where timestamp.string is not null and item.string = 'Pizza'") sql_results.show() Using full fidelity schema with SQL You can use the following syntax example, with the same docu...