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Build vs Buy a Data Quality Solution: Which is Best for You? Gain insights on a hybrid approach. Download white paper now! You find this anmldelse often used in conjunction with faceting. Filter queries make anmfldelse of a filterCache see solrconfig. Often, using NOW in filter queries causes this caching to be useless. There will be two entries sidee the Dating sider anmeldelse solr?d, something like: But anmeldelsd of a diversion… OK, you mentioned dates.
Get to the point. Be careful when using NOW! In the above example, date: This translates into a form like: The fq clause now looks something like: Bare NOW entries in filter clauses will pretty Dating sider anmeldelse solr?d guarantee that the cached result sets will never be reused. What do you do to make it better? Using midnight can make sense from two perspectives.
So just using NOW for the lower bound would miss anything published between midnight and whenever the user happens to submit the query on the day in this example of the lower bound. These clauses are invariant until after midnight tonight so these clauses will return the same results all day today, and only the first submission of this fq will incur the cost of figuring out which documents satisfy it, all the queries after the first will just read the cached result set from the filterCache.
If your index has dates in the future, you may get them too. The above technique will show documents that will be officially published at, say, A couple of notes about dates: Before I finish, a couple of notes about dates. Use the coarsest dates you can and still satisfy your use case. The sorting resource requirements go up by the number of unique terms. So storing millisecond resolution when all you care about is day can be wasteful.
This is also true when faceting. The above examples in the 3. An exercise for the reader: What are the consequences of using different kinds of rounding? Maintaining high quality data is essential for operational efficiency, meaningful analytics and good long-term customer relationships. But, when dealing with multiple sources of data, data quality becomes complex, so you need to know when you should build a custom data quality tools effort over canned solutions.
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