![]() ![]() The results are obviously not what we need, we get the phrases where ‘real’ is only a part of the word: Task: find records where keywords contain a target word.įirst solution that you might think about could look like this: SELECT url, keyword, tokens įor real-world Snowflake tables you should also define a clustering key, but for simplicity I omitted these details. A complete list of data types can be found in Snowflake Documentation. Snowflake supports most standard data types that you normally have in SQL. The examples below will be based on the following table: In the article below I would like to share these insights with those who would like to use Snowflake in their projects. While implementing features for the Conductor platform, we came across a number of tricky Snowflake queries. Another benefit of Snowflake is that the queries are written with SQL and some Snowflake-specific extensions which developers should be comfortable with.Įvery technology has its limitations, pros, and cons. Compared to other tools, Snowflake satisfies our requirements for heavy OLAP and provides a flexible pricing model. ![]() Snowflake is a modern data warehouse that we use to power some of the core features of the Conductor platform – Domain and Page Explorer which analyze millions of keywords per user request. At Conductor, we deal with pretty big data sets and provide users with a rich set of data views, filtering, and aggregations – all in real-time! ![]()
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