Sorry I missed this one
In the context what has been changed we ought to have an additional column
timestamp
In short we can have
datachange(object_name, partition_name, colname, timestamp)
timestamp is the point in time you want to compare against for changes.
Example
SELECT * FROM <TABLE> WHERE datachange('<TABLE>', '2023-08-01 00:00:00') = 1
This query should return all rows from the <TABLE> table that have been
changed since June 1, 2023, 00:00:00.
Let me know your thoughts
HTH
Mich Talebzadeh,
Distinguished Technologist, Solutions Architect & Engineer
London
United Kingdom
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On Wed, 30 Aug 2023 at 10:19, Mich Talebzadeh <mich.talebza...@gmail.com>
wrote:
> Another idea that came to my mind from the old days, is the concept of
> having a function called *datachange*
>
> This datachange function should measure the amount of change in the data
> distribution since ANALYZE STATISTICS last ran. Specifically, it should
> measure the number of inserts, updates and deletes that have occurred on
> the given object and helps us determine if running ANALYZE STATISTICS would
> benefit the query plan.
>
> something like
>
> select datachange(object_name, partition_name, colname)
>
> Where:
>
> object_name – is the object name. fully qualified objectname. The
> object_name cannot be null.
> partition_name – is the data partition name. This can be a null value.
> colname – is the column name for which the datachange is requested. This
> can be a null value (meaning all columns)
>
> This should be expressed as a percentage of the total number of rows in
> the table or partition (if the partition is specified). The percentage
> value can be greater than 100% because the number of changes to an object
> can be much greater than the number of rows in the table, particularly when
> the number of deletes and updates to a table is very high.
>
> So we can run this function to see if ANALYZE STATISTICS is required on a
> certain column.
>
> HTH
>
> Mich Talebzadeh,
> Distinguished Technologist, Solutions Architect & Engineer
> London
> United Kingdom
>
>
> view my Linkedin profile
>
>
> https://en.everybodywiki.com/Mich_Talebzadeh
>
>
>
> Disclaimer: Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
> Mich Talebzadeh,
> Distinguished Technologist, Solutions Architect & Engineer
> London
> United Kingdom
>
>
> view my Linkedin profile
> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>
>
> https://en.everybodywiki.com/Mich_Talebzadeh
>
>
>
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>
>
> On Wed, 30 Aug 2023 at 00:49, Chetan <chetansuttra...@gmail.com> wrote:
>
>> Thanks for the detailed explanation.
>>
>>
>> Regards,
>> Chetan
>>
>>
>>
>> On Tue, Aug 29, 2023, 4:50 PM Mich Talebzadeh <mich.talebza...@gmail.com>
>> wrote:
>>
>>> OK, let us take a deeper look here
>>>
>>> ANALYSE TABLE mytable COMPUTE STATISTICS FOR COLUMNS *(c1, c2), c3*
>>>
>>> In above, we are *explicitly grouping columns c1 and c2 together for
>>> which we want to compute statistic*s. Additionally, we are also *computing
>>> statistics for column c3 independen*t*ly*. This approach *allows CBO to
>>> treat columns c1 and c2 as a group and compute joint statistics for them,
>>> while computing separate statistics for column c3.*
>>>
>>> If columns c1 and c2 are frequently used together in conditions, I
>>> concur it makes sense to compute joint statistics for them by using the
>>> above syntax. On the other hand, if each column has its own significance
>>> and the relationship between them is not crucial, we can use
>>>
>>> ANALYSE TABLE mytable COMPUTE STATISTICS FOR COLUMNS
>>> *c1, c2, c3*
>>>
>>> This syntax can be used to compute separate statistics for each column.
>>>
>>> So your mileage varies.
>>>
>>> HTH
>>>
>>> Mich Talebzadeh,
>>> Distinguished Technologist, Solutions Architect & Engineer
>>> London
>>> United Kingdom
>>>
>>>
>>> view my Linkedin profile
>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>
>>>
>>> https://en.everybodywiki.com/Mich_Talebzadeh
>>>
>>>
>>>
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>>> disclaimed. The author will in no case be liable for any monetary damages
>>> arising from such loss, damage or destruction.
>>>
>>>
>>>
>>>
>>> On Tue, 29 Aug 2023 at 12:14, Chetan <chetansuttra...@gmail.com> wrote:
>>>
>>>> Hi,
>>>>
>>>> If we are taking this up, then would ask can we support multicolumn
>>>> stats such as :
>>>> ANALYZE TABLE mytable COMPUTE STATISTICS FOR COLUMNS (c1,c2), c3
>>>> This should help in estimating better for conditions involving c1 and c2
>>>>
>>>> Thanks.
>>>>
>>>> On Tue, 29 Aug 2023 at 09:05, Mich Talebzadeh <
>>>> mich.talebza...@gmail.com> wrote:
>>>>
>>>>> short answer on top of my head
>>>>>
>>>>> My point was with regard to Cost Based Optimizer (CBO) in traditional
>>>>> databases. The concept of a rowkey in HBase is somewhat similar to that of
>>>>> a primary key in RDBMS.
>>>>> Now in databases with automatic deduplication features (i.e. ignore
>>>>> duplication of rowkey), inserting 100 rows with the same rowkey actually
>>>>> results in only one physical entry in the database due to deduplication.
>>>>> Therefore, the new statistical value added should be 1, reflecting the
>>>>> distinct physical entry. If the rowkey is already present in HBase, the
>>>>> value would indeed be 0, indicating that no new physical entry was
>>>>> created.
>>>>> We need to take into account the underlying deduplication mechanism of the
>>>>> database in use to ensure that statistical values accurately represent the
>>>>> unique physical data entries.
>>>>>
>>>>> HTH
>>>>>
>>>>> Mich Talebzadeh,
>>>>> Distinguished Technologist, Solutions Architect & Engineer
>>>>> London
>>>>> United Kingdom
>>>>>
>>>>>
>>>>> view my Linkedin profile
>>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>>
>>>>>
>>>>> https://en.everybodywiki.com/Mich_Talebzadeh
>>>>>
>>>>>
>>>>>
>>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>>>> any loss, damage or destruction of data or any other property which may
>>>>> arise from relying on this email's technical content is explicitly
>>>>> disclaimed. The author will in no case be liable for any monetary damages
>>>>> arising from such loss, damage or destruction.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> On Tue, 29 Aug 2023 at 02:07, Jia Fan <fanjia1...@gmail.com> wrote:
>>>>>
>>>>>> For those databases with automatic deduplication capabilities, such
>>>>>> as hbase, we have inserted 100 rows with the same rowkey, but in fact
>>>>>> there
>>>>>> is only one in hbase. Is the new statistical value we added 100 or 1, or
>>>>>> hbase already contains this rowkey, the value would be 0. How should we
>>>>>> handle this situation?
>>>>>>
>>>>>> Mich Talebzadeh <mich.talebza...@gmail.com> 于2023年8月29日周二 07:22写道：
>>>>>>
>>>>>>> I have never been fond of the notion that measuring inserts,
>>>>>>> updates, and deletes (referred to as DML) is the sole criterion for
>>>>>>> signaling a necessity to update statistics for Spark's CBO.
>>>>>>> Nevertheless,
>>>>>>> in the absence of an alternative mechanism, it seems this is the only
>>>>>>> approach at our disposal (can we use AI for it 😁). Personally, I would
>>>>>>> prefer some form of indication regarding shifts in the distribution of
>>>>>>> values in the histogram, overall density, and similar indicators. The
>>>>>>> decision to execute "ANALYZE TABLE xyz COMPUTE STATISTICS FOR COLUMNS"
>>>>>>> revolves around column-level statistics, which is why I would tend to
>>>>>>> focus
>>>>>>> on monitoring individual column-level statistics to detect any signals
>>>>>>> warranting a statistics update.
>>>>>>> HTH
>>>>>>>
>>>>>>> Mich Talebzadeh,
>>>>>>> Distinguished Technologist, Solutions Architect & Engineer
>>>>>>> London
>>>>>>> United Kingdom
>>>>>>>
>>>>>>>
>>>>>>> view my Linkedin profile
>>>>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>>>>
>>>>>>>
>>>>>>> https://en.everybodywiki.com/Mich_Talebzadeh
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility
>>>>>>> for any loss, damage or destruction of data or any other property which
>>>>>>> may
>>>>>>> arise from relying on this email's technical content is explicitly
>>>>>>> disclaimed. The author will in no case be liable for any monetary
>>>>>>> damages
>>>>>>> arising from such loss, damage or destruction.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Sat, 26 Aug 2023 at 21:30, Mich Talebzadeh <
>>>>>>> mich.talebza...@gmail.com> wrote:
>>>>>>>
>>>>>>>> Hi,
>>>>>>>>
>>>>>>>> Impressive, yet in the realm of classic DBMSs, it could be seen as
>>>>>>>> a case of old wine in a new bottle. The objective, I assume, is to
>>>>>>>> employ
>>>>>>>> dynamic sampling to enhance the optimizer's capacity to create
>>>>>>>> effective
>>>>>>>> execution plans without the burden of complete I/O and in less time.
>>>>>>>>
>>>>>>>> For instance:
>>>>>>>> ANALYZE TABLE xyz COMPUTE STATISTICS WITH SAMPLING = 5 percent
>>>>>>>>
>>>>>>>> This approach could potentially aid in estimating deltas by
>>>>>>>> utilizing sampling.
>>>>>>>>
>>>>>>>> HTH
>>>>>>>>
>>>>>>>> Mich Talebzadeh,
>>>>>>>> Distinguished Technologist, Solutions Architect & Engineer
>>>>>>>> London
>>>>>>>> United Kingdom
>>>>>>>>
>>>>>>>>
>>>>>>>> view my Linkedin profile
>>>>>>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>>>>>>
>>>>>>>>
>>>>>>>> https://en.everybodywiki.com/Mich_Talebzadeh
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> *Disclaimer:* Use it at your own risk. Any and all responsibility
>>>>>>>> for any loss, damage or destruction of data or any other property
>>>>>>>> which may
>>>>>>>> arise from relying on this email's technical content is explicitly
>>>>>>>> disclaimed. The author will in no case be liable for any monetary
>>>>>>>> damages
>>>>>>>> arising from such loss, damage or destruction.
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On Sat, 26 Aug 2023 at 20:58, RAKSON RAKESH <raksonrak...@gmail.com>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> Hi all,
>>>>>>>>>
>>>>>>>>> I would like to propose the incremental collection of statistics
>>>>>>>>> in spark. SPARK-44817
>>>>>>>>> <https://issues.apache.org/jira/browse/SPARK-44817> has been
>>>>>>>>> raised for the same.
>>>>>>>>>
>>>>>>>>> Currently, spark invalidates the stats after data changing
>>>>>>>>> commands which would make CBO non-functional. To update these stats,
>>>>>>>>> user
>>>>>>>>> either needs to run `ANALYZE TABLE` command or turn
>>>>>>>>> `spark.sql.statistics.size.autoUpdate.enabled`. Both of these ways
>>>>>>>>> have
>>>>>>>>> their own drawbacks, executing `ANALYZE TABLE` command triggers full
>>>>>>>>> table
>>>>>>>>> scan while the other one only updates table and partition stats and
>>>>>>>>> can be
>>>>>>>>> costly in certain cases.
>>>>>>>>>
>>>>>>>>> The goal of this proposal is to collect stats incrementally while
>>>>>>>>> executing data changing commands by utilizing the framework
>>>>>>>>> introduced in
>>>>>>>>> SPARK-21669 <https://issues.apache.org/jira/browse/SPARK-21669>.
>>>>>>>>>
>>>>>>>>> SPIP Document has been attached along with JIRA:
>>>>>>>>>
>>>>>>>>> https://docs.google.com/document/d/1CNPWg_L1fxfB4d2m6xfizRyYRoWS2uPCwTKzhL2fwaQ/edit?usp=sharing
>>>>>>>>>
>>>>>>>>> Hive also supports automatic collection of statistics to keep the
>>>>>>>>> stats consistent.
>>>>>>>>> I can find multiple spark JIRAs asking for the same:
>>>>>>>>> https://issues.apache.org/jira/browse/SPARK-28872
>>>>>>>>> https://issues.apache.org/jira/browse/SPARK-33825
>>>>>>>>>
>>>>>>>>> Regards,
>>>>>>>>> Rakesh
>>>>>>>>>
>>>>>>>>
>>>>
>>>> --
>>>> --
>>>> Regards,
>>>> Chetan
>>>>
>>>> +353899475147
>>>> +919665562626
>>>>
>>>>
