{"height":"190","blog_url":"https://ktr89-en.hatenadiary.jp/","description":"Introduction In data processing context, we often use query with URL condition. For example, using Google Analytics URL parameters you can measure where your site's users are from(Search Engine, Listing Ad or Display Ad, etc.). Forward-matching query is useful for that query. In this article, I try \u2026","provider_url":"https://hatena.blog","type":"rich","title":"Speeding up URL forward-matching Query by splitting schema ","image_url":null,"provider_name":"Hatena Blog","author_name":"ktr89","published":"2019-10-01 12:00:00","blog_title":"Data is Nutritious","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fktr89-en.hatenadiary.jp%2Fentry%2F2019%2F10%2F01%2F120000\" title=\"Speeding up URL forward-matching Query by splitting schema  - Data is Nutritious\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","url":"https://ktr89-en.hatenadiary.jp/entry/2019/10/01/120000","width":"100%","version":"1.0","categories":["Scala","DataProcessing"],"author_url":"https://blog.hatena.ne.jp/ktr89/"}