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Myrddin Emrys's user avatar
Myrddin Emrys's user avatar
Myrddin Emrys's user avatar
Myrddin Emrys
  • Member for 13 years, 4 months
  • Last seen more than 3 years ago
  • Wisconsin
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Handling newsletter mail subscribers data
Can you please explain the questions again? I do not understand what you are asking. I know English is not your first language, and I apologize since you are far better at English than I am in any second language, but if you can clean up the question's grammar (perhaps with the assistance of another local developer who has more experience with English) it would help us answer it.
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What type of datastore should I use for high volume time series data?
That still doesn't answer the question of whether this method is an improvement over a direct connection to the database and normal inserts, particularly since the user presumably must have indexing or they will be unable to get any useful information back out of the database... this is 129 billion entries per month at this rate. Do you want to query a 129 billion line table with no index?
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What type of datastore should I use for high volume time series data?
Can MySQL and/or PostgreSQL handle a 50k line LOAD DATA INFILE once per second? Is that command faster than direct writes to the database?
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What type of datastore should I use for high volume time series data?
So your answer is that batch processing isn't a good choice because the measurements won't ever stop, correct? They will be processed constantly, so the read portion of the database needs to keep up?
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How can I select all online friends?
SQL optimization that databases perform works better the simpler and more predictable your query; less common join methods, such as @mrdenny suggested, make it difficult for the database server to optimize well. Also... this is a tiny table. Don't worry about bloating it. Even with billions of friends, indexing will make queries against this table a snap.
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