Average for periods of 3 hours

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• How to calculate daily, hourly average for the very large data set?

  Some_Timestamp	"Parameter1"	Parameter2
  1 JANUARY 2015 02:00. 00:000000 AM - 07:00	2341.4534	676341.4534
  1 JANUARY 2015 02:00. 01:000000 AM - 07:00	2341.4533	676341.3
  1 JANUARY 2015 03:04. 01:000000 PM - 07:00	5332.3533	676341.53
  1 JANUARY 2015 03:00. 01:000046 PM - 07:00	23.34	36434.4345
  JANUARY 2, 2015 05:06.01:000236 AM - 07:00	352.33	43543.4353
  JANUARY 2, 2015 09:00. 01:000026 AM - 07:00	234.45	3453.54
  3 FEBRUARY 2015 10:00. 01:000026 PM - 07:00	3423.353	4634.45
  FEBRUARY 4, 2015 11:08. 01:000026 AM - 07:00	324.35325	34534.53

  We have data as above a table and we want to calculate all the days, the hourly average for large data set (almost 100 million).  Is it possible to use the sql functions of analysis for better performance instead of the ordinary average and group of?  Or any other way better performance?

  Don't know if that works better, but instead of using to_char, you could use trunc. Try something like this:

  select
      trunc(some_timestamp,'DD'),
      avg(parameter1)
  from
     bigtable
  where
     some_timestamp between systimestamp-180 and systimestamp
  group by
     trunc(some_timestamp,'DD');
  

  Hope that helps,

  dhalek

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• Statistics calculation of schema for a huge 10 hours batch

  Hello

  We are on gR 11, 2 (11.2.0.4) Oracle Linux. The integrated schema statistics collection job is configured to run only during the night now in production.

  We have a huge batch moving a very large amount of data in almost 90% of the tables in the database (only get tables are not affected). It will take about 10 hours and is scheduled over the weekend. It's a big ETL process that moves a huge amount of data from a database (source) to another (target) database.  How can I go to ensure that schema statistics are updated when this heavy DML constantly occurs during this period of 10-hour day?  What is the best practice to adopt in such a scenario? What I read in the Oracle documentation, which is

  "For tables that are loaded in bulk, procedures for the collection of statistics must be run on these tables immediately after the loading process, preferably as part of the same script or job that executes the bulk loading.

  How to batch? One option is to "divide the lots say 5 equal pieces" and after that each piece is finished, run the stats together. What is the best way to do it?

  I will be grateful for the entries on it.

  Thank you

  OrauserN

  We have a huge batch moving a very large amount of data in almost 90% of the tables in the database (only get tables are not affected). It will take about 10 hours and is scheduled over the weekend. It's a big ETL process that moves a huge amount of data from a database (source) to another (target) database.

  OK - but this does not explain why you have a question about what stats should be executed. And you do not mention what system, the source or the target. your stats is everything.

  How can I go to ensure that schema statistics are updated when this heavy DML constantly occurs during this period of 10-hour day?  What is the best practice to adopt in such a scenario? What I read in the Oracle documentation, which is

  "For tables that are loaded in bulk, procedures for the collection of statistics must be run on these tables immediately after the loading process, preferably as part of the same script or job that executes the bulk loading.

  The recommendation is ONLY for the use case where there is a concomitant use of these ' tables that are loaded in bulk.

  Yet once, you did not mention ANY use of the data in the systems of your source or target. Without knowing how the data is used DURING THE MOVE, we can give advice:

  1. what 'pass' given average to you? You are "suppressing" the data from the source system and "insert" then the same data in the target system? Or you just ' data are copied "from source to the target?

  2 users perform DML on tables of source? If data comes to be SELECTED from those tables and not deleted, so you need not to run statistics on the source system.

  3. users perform DML on target tables? What is DML performed during loading the new data? Then the load might affect the performance of the executed DML.

  How to batch? One option is to "divide the lots say 5 equal pieces" and after that each piece is finished, run the stats together. What is the best way to do it?

  Who knows? You have not even told us:

  1. what system, source or target or both, you are talking about

  2. What does batch processing

  3. what DML is to be carried out at the same time as the treatment by lots

  Much depends on the type of DML performed and used tables and the structure of lots. It could be that a step-by-step process could be used. That would be a bit similar to what you proposed except that he wouldn't use the table stats, stats of schema:

  1. run the part of lot 1 which updates some tables that uses certain DML

  2. collect statistics table on the tables affected by part 1 - which minimizes the effect of 'statistics' in this part of the load

  3. run the part of lot 2 that updates some different tables that affect different DML

  4 collect statistics table on the tables affected by part 2

  5 and so on

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• Averages for number of loops

  Hi all

  I have a code (attached) in which a triangular wave is supposed to a magnetic field of ramp up and down to very low frequency (0.1 Hz or low). Reading (X) vs keithley reading field (Y) represented by two random numbers generators must be taken in synchronization with the triangular wave point by point. I would be very grateful if you could help to achieve the following objectives:

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  Thank you

  Hadi

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  Hello
   
   
  1. remember you number updates that have been installed?
   
   
   
  First check to see if there are external devices attached to the computer, if so remove and check.
   
  Method 1.
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  Troubleshooting in safe mode
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  If we are able to boot to the desktop now, I would ask you install the updates one by one andcheck the update is at the origin of the conflict.

   

   

   
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  Kind regards
  Support Microsoft Savan-

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