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From:Karen Abgarian <abvk Date:May 7 2012 5:51pm
Subject:Re: 回复: Why is creating inde
xes faster after inserting massive data rows?
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Good point about key buffer.   I was only thinking about the table updates for MyISAM, not
indexes.   The being stuck waiting for buffer flush could also happen.  However, for the
table blocks this would be the same issue as with load followed by index rebuild, and for
the indexes, it will have to be compared, performance-wise, with an expense of sorting an
equally sized index.   

On May 7, 2012, at 10:40 AM, Rick James wrote:

> (Correction to Karen's comments)
> * MyISAM does all its index operations in the key_buffer, similar to InnoDB and its
> buffer_pool.
> * Yes, writes are delayed (in both engines), but not forever.  If the table is huge,
> you will eventually be stuck waiting for blocks to be flushed from cache.
> * If the table is small enough, all the I/O can be delayed, and done only once.  So
> yes, the in-memory cache may be faster. 
> 
> Based on this discussion, you should note that "random" indexes, such as GUIDs, MD5s,
> etc, tend to 
> 
> 
>> -----Original Message-----
>> From: Karen Abgarian [mailto:abvk@stripped]
>> Sent: Monday, May 07, 2012 10:31 AM
>> To: mysql@stripped
>> Subject: Re: 回复: Why is creating indexes faster after inserting
>> massive data rows?
>> 
>> Hi,
>> 
>> A couple cents to this.
>> 
>> There isn't really a million of block writes.   The record gets added
>> to the block, but that gets modified in OS cache if we assume MyISAM
>> tables and in the Innodb buffer if we assume InnoDB tables.   In both
>> cases, the actual writing does not take place and does not slow down
>> the process.    What does however happen for each operation, is
>> processing the statement, locating the entries to update in the index,
>> index block splits and , for good reason, committing.
>> 
>> When it comes to creating an index, what needs to happen, is to read
>> the whole table and to sort all rows by the index key.   The latter
>> process will be the most determining factor in answering the original
>> question, because for the large tables the sort will have to do a lot
>> of disk I/O.    The point I am trying to make is there will be
>> situations when creating indexes and then inserting the rows will be
>> faster than creating an index afterwards.   If we try to determine such
>> situations, we could notice that the likelihood of the sort going to
>> disk increases with the amount of distinct values to be sorted.   For
>> this reason, my choice would be to create things like primary/unique
>> keys beforehand unless I am certain that everything will fit in the
>> available memory.
>> 
>> Peace
>> Karen
>> 
>> 
>> 
>> On May 7, 2012, at 8:05 AM, Johan De Meersman wrote:
>> 
>>> ----- Original Message -----
>>> 
>>>> From: "Zhangzhigang" <zzgang_2008@stripped>
>>> 
>>>> Ok, Creating the index *after* the inserts, the index gets created
>> in
>>>> a single operation.
>>>> But the indexes has to be updating row by row after the data rows
>> has
>>>> all been inserted. Does it work in this way?
>>> No, when you create an index on an existing table (like after a mass
>> insert), what happens is that the engine does a single full tablescan
>> and builds the index in a single pass, which is a lot more performant
>> than updating a single disk block for every record, for the simple
>> reason that a single disk block can contain dozens of index entries.
>>> 
>>> Imagine that you insert one million rows, and you have 100 index
>> entries in a disk block (random numbers, to make a point. Real numbers
>> will depend on storage, file system, index, et cetera). Obviously
>> there's no way to write less than a single block to disk - that's how
>> it works.
>>> 
>>> You can update your index for each record in turn. That means you
>> will need to do 1 million index - and thus block - writes; plus
>> additional reads for those blocks you don't have in memory - that's the
>> index cache.
>>> 
>>> Now, if you create a new index on an existing table, you are first of
>> all bypassing any index read operations - there *is* no index to read,
>> yet. Then the system is going to do a full tablescan - considered slow,
>> but you need all the data, so there's no better way anyway. The index
>> will be built - in-memory as much as possible - and the system will
>> automatically prefer to write only complete blocks - 10.000 of them.
>> That's the exact same number of index blocks, but you only write each
>> block once, so that's only 10.000 writes instead of 1.000.000.
>>> 
>>> Now there's a lot more at play, things like B-tree balancing and
>> whatnot, but that's the basic picture.
>>> 
>>> --
>>> 
>>> Bier met grenadyn
>>> Is als mosterd by den wyn
>>> Sy die't drinkt, is eene kwezel
>>> Hy die't drinkt, is ras een ezel
>> 
>> 
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> 

Thread
Why is creating indexes faster after inserting massive data rows?Zhangzhigang7 May
  • Re: Why is creating indexes faster after inserting massive data rows?Ananda Kumar7 May
    • 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang7 May
  • Re: Why is creating indexes faster after inserting massive data rows?Johan De Meersman7 May
    • 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang7 May
      • Re: 回复: Why is creating indexes faster after inserting massive data rows?Alex Schaft7 May
        • 回复: 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang7 May
          • Re: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Claudio Nanni7 May
            • too nice not to share it!hsv2 Oct
          • Re: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Mihamina Rakotomandimby30 May
      • Re: 回复: Why is creating indexes faster after inserting massive data rows?Claudio Nanni7 May
        • 回复: 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang7 May
      • Re: 回复: Why is creating indexes faster after inserting massive data rows?Johan De Meersman7 May
        • RE: 回复: Why is creating indexes faster after inserting massive data rows?Rick James7 May
        • Re: 回复: Why is creating indexes faster after inserting massive data rows?Karen Abgarian7 May
          • 回复: 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang8 May
            • Re: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Karen Abgarian8 May
              • 回复: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang8 May
                • Re: 回复: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Johan De Meersman8 May
                  • 回复: 回复: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang8 May
                  • Re: 回复: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Karen Abgarian8 May
                    • 回复: 回复: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang9 May
              • RE: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Rick James10 May
            • Re: 回复: 回复: Why is creating indexes faster after inserting massive data rows?Johan De Meersman8 May
        • Re: 回复: Why is creating indexes faster after inserting massive data rows?Karen Abgarian7 May
    • RE: Why is creating indexes faster after inserting massive datarows?Rick James7 May
      • 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang9 May
        • RE: 回复: Why is creating indexes faster after inserting massive data rows?Rick James9 May
          • Re: 回复: Why is creating indexes faster after inserting massive data rows?Claudio Nanni9 May
          • 回复: 回复: Why is creating indexes faster after inserting massive data rows?Zhangzhigang10 May