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You have to choose one of the terminal stations as origin and store the distances from origin to the each station on the route: +--------------+----------------------+ | Station Name | Distance from origin | +--------------+----------------------+ | Station A | 0 | | Station B | 10 | | Station C | ...


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Neo4j is a database that sounds a fit for your needs. It is graph based database, there are many drivers for it in many languages and it is built in Java. In this database, you would specify the relationships within each node, rather than creating tables for joins, like in mySQL.


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Computers can't operate the real sets. In fact - nobody can. We don't know how to fetch only required items that satisfied the given conditions from the bag without iterations. Formal relational model is an abstraction. RDBMSes are just resemble it but they are built on the completely different basis. They uses lists, they iterate and they uses rows of ...


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The major differences are related to duplicate entries in both data and metadata, and the existence of NULL values. SQL implementations deviate from the relational model for practical reasons, for the most part. Read up on the topic in SQL and Relational Theory by C.J. Date or (Kudos to Bill Karwin for this title by the same author) read pages 2 and 3 in ...


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I tested few databases for the similar scenario (ingesting logs), and MongoDB seems to be quite useful. I used following collection: db.createCollection("apache", {capped: true, size: 10000000000}); It seems that once the collection is capped it is not growing any more. Now there is a tricky part - retrieving the data. If you need to query periods of ...


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How unique are the DataID's? Are there just a handful of DataID's for the 20 million entries per hour or are DataID's more numerous? But if your most frequent query is based on a narrow time frame first and then specific DataID's then this create statement should give you decent performance. You will need to change the data types to what makes sense for ...


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In addition to what Jynus said: be sure your table is physically clustered on Date first. This will make range scans very efficient, so aggregation up to weeks or months will be fast. Even if you choose to instantiate these week- or month-level totals in summary tables, clustering by date will help by making the updates very quick. This kind of situation ...


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With respect to your question about using Vertica during the ETL, it's very rarely necessary (although not unknown) to use a different type of database for the ETL. I would not do that unless you perceive a specific need to do so. The only times I've ever heard of this being done due to interactions with legacy data sources. Although @Kermit works with ...


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I'm going to assume that you already have the budget to implement some data warehouse solution. Just briefly talking about Vertica; it is a load and read optimized platform, and certainly not designed for OLTP. The piece on staging and processing data would need some more thought. Vertica isn't really designed to have data staged, cleansed, and moved into ...


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I sat down with management and said, "alright, what's the goal here?" Once we talked about it, they decided to let me write it in Python and use Postgres, since we use Postgres internally. I was able to convince them of that because of the dynamic libraries and the fact that I can tune the instance to cache everything and keep it in memory. So...a highly ...


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I can only say that you have my deepest sympathies. Doesn't the person/company who/which is getting you to write a tool under this mind-boggling constraint realise that you'll have to do far more work for a far lesser return than if you used (as you say) "Python, Perl...". Anyway, what you wrote rang a very old bell in my memory cells - I remembered having ...


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Use the official sample databases from MySQL: http://dev.mysql.com/doc/index-other.html.



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