Google Cloud Spanner Regular Expression Functions

The regular expressions are commonly used to identify the precise pattern of the characters in the string. Many popular programming languages such as Python, Java, R, etc. extensively use regular expression functions. You can also use regular expression to validate strings, for example, extracting numbers from the string values. In this article, we will check regular expression functions supported in cloud spanner. Cloud Spanner Regular Expression Functions The regular expression functions in cloud spanner are string functions that match a given regular expression. These functions are commonly called as a…

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Hive Extract Numbers using Regular Expression Functions

In my other article, we have seen how to extract date values from a string using Hive regular expressions. The regular expression function is sometime called as regex. The other common uses of regular expression is to extract the numeric values. For example, extract area code or phone numbers from the string data. In this article, we will check how to extract numbers using regular expression functions in Apache Hive. Extract Numbers using Hive Regular Expression Functions When you work on different data sources, you may get requirement to extract…

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Hive Extract Date using Regular Expression Functions

In my other articles, we have seen how regular expression functions are used to check if a string is numeric. The other common requirements is to extract the date field from the string using Hive regular expression functions. For example, you may get requirement to get date value from the string field. Apache Hive support many functionalities that you can use to extract date type. But, using a regular expression function to extract date from a string is the easiest method. Extract Date using Hive Regular Expression Functions There are…

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Snowflake Extract Date using Regular Expression Functions

In my other article, we have seen how to extract number or numeric values from a string. The other common requirement is to extract date from a string data. For example, you may get requirement to extract date of birth from the string field. Snowflake supports various date functions to validate a date value. In this article, we will check how to extract date from a string field using Snowflake regular expression functions. Extract Date using Snowflake Regular Expression Functions In my other article, we have discussed on Snowflake regular…

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Snowflake Extract Numbers using Regular Expression Functions

There are various requirements to extract numbers from string value. This requirement comes when you work with different data source. For example, heterogeneous data may contain many unwanted values and requirements will be to get only numbers or numeric values. Snowflake supports many built-in and regular expression functions. In this article, we will check how to extract numbers or numeric values from a string using Snowflake regular expression functions. Extract Numbers using Snowflake Regular Expression Functions In my other article, we have discussed on Snowflake regular expressions. We will use…

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Snowflake Regular Expression Functions and Examples

The regular expressions are commonly used functions in programming languages such as Python, Java, R, etc. The Snowflake regular expression functions identify the precise pattern of the characters in given string. Regular expressions are commonly used in validating strings, for example, extracting numbers from the string values, etc. In this article, we will check the supported Regular expression functions in Snowflake. Snowflake Regular Expression Functions The regular expression functions are string functions that match a given regular expression. These functions are commonly called as a 'regex' functions. Below are some…

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Redshift Pattern Matching Conditions – LIKE, SIMILAR TO, POSIX Operators

Amazon Redshift supports several pattern matching techniques that you can use to search for specific strings or patterns of characters within your data. Redshift Pattern Matching Amazon Redshift pattern matching conditions are used to search a string for a given pattern. You can search for the string by matching particular patterns. Page Contents Introduction to Redshift Redshift Pattern Matching - Syntax and Examples Redshift Pattern Matching Performance Considerations Conclusion Introduction to Redshift Amazon Redshift is a fully managed cloud-based data warehousing solution designed for large-scale data processing and analysis. It's…

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Amazon Redshift isnumeric Alternative and Examples

When you work with heterogeneous data set, you may have to filter out unwanted data before loading it to the actual data warehouse table. For example, you many have field1 of type string contains alphanumeric values. You may get requirement to filter out non-numeric values. In this article, we will check Amazon Redshift isnumeric alternative with some examples. Amazon Redshift isnumeric Function Many databases such as SQL server supports isnumeric built-in functions. As of now, AWS Redshift does not support isnumeric function. You have to use an alternative approach such…

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Vertica Regular Expression Functions and Examples

The Vertica regular expression functions are used to identify a precise pattern from the given string. The string could be variable or database table column name. The regular expressions are used in various applications such as extracting some numbers from string values, extracting alphanumeric values from string, extracting particular pattern from string, validating received data. You can also use regular expression to validate date, range check, extract only digits from given string etc. You can use regular expression functions along with any built-in functions such as date type conversion functions,…

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