Hi Ramkrishna,

Thank you for your inputs! Unfortunately we would not be knowing the column names beforehand. We had generated the above scenario for illustration purposes.

The intent of our query is that, given a single row key, a start column key and an end column key, scan for the columns that are between the two column keys.  We have been achieving that by using ColumnRangeFilter. Our write pattern would be Put followed by Delete immediately (Keep_deleted_cells is set to false). So as more Deletes start to accumulate, we notice the scan time starts to be very long and the cpu shoots up to 100% for a core during every scan. On trying to debug we observed the following behavior:

At any instant, the cells of the particular row would be roughly organized like

D1 P1 D2 P2 D3 P3 ............ Dn-1 Pn-1 Dn Pn Pn+1 Pn+2 Pn+3 Pn+4....

where D and P are Delete and it's corresponding Put. The newer values from Pn haven't been deleted yet.

As the scan initiates, inside the StoreScanner, NormalUserScanQueryMatcher would match the first cell (D1). It would be added to the DeleteTracker and a MatchCode of SKIP is returned. Now for the next cell (P1) the matcher would check with the DeleteTracker and return a code of SEEK_NEXT_COL. Again the next cell would be D2 and this would happen alternately. No filter is applied. This goes on till it encounters Pn where filter is applied, SEEK_NEXT_USING_HINT is done and now reseek happens to position near the desired range. The result is returned quickly after that.

The SKIP iterations happen a lot because our pattern would have very less active cells and only towards the latest column qualifiers(ordered high lexicographically). We were wondering if the query could be modified so that the filter could be applied initially or some other way to seek to the desired range directly.

Regards,
Solvannan R M


On 2019/09/13 15:53:51, ramkrishna vasudevan wrote:
> Hi>
> Generally if you can form the column names like you did in the above case>
> it is always better you add them using>
> scan#addColumn(family, qual). I am not sure of the shell syntax to add>
> multiple columns but am sure there is a provision to do it.>
>
> This will ensure that the scan starts from the given column and fetches the>
> required column only. In your case probably you need to pass a set of>
> qualifiers (instead of just 1).>
>
> Regards>
> Ram>
>
> On Fri, Sep 13, 2019 at 8:45 PM Solvannan R M >
> wrote:>
>
> > Hi Anoop,>
> >>
> > We have executed the query with the qualifier set like you advised.>
> > But we dont get the results for the range but only the specified>
> > qualifier cell is returned.>
> >>
> > Query & Result:>
> >>
> > hbase(main):008:0> get 'mytable', 'MY_ROW',>
> > {COLUMN=>["pcf:\x00\x16\xDFx"],>
> > FILTER=>ColumnRangeFilter.new(Bytes.toBytes(1499000.to_java(:int)),>
> > true, Bytes.toBytes(1499010.to_java(:int)), false)}>
> > COLUMN CELL>
> > pcf:\x00\x16\xDFx timestamp=1568380663616,>
> > value=\x00\x16\xDFx>
> > 1 row(s) in 0.0080 seconds>
> >>
> > hbase(main):009:0>>
> >>
> >>
> > Is there any other way to get arond this ?.>
> >>
> >>
> > Regards,>
> >>
> > Solvannan R M>
> >>
> >>
> > On 2019/09/13 04:53:45, Anoop John wrote:>
> > > Hi>>
> > > When you did a put with a lower qualifier int (put 'mytable',>>
> > > 'MY_ROW', "pcf:\x0A", "\x00") the system flow is getting a valid cell>
> > at>>
> > > 1st step itself and that getting passed to the Filter. The Filter is>
> > doing>>
> > > a seek which just avoids all the in between deletes and puts>
> > processing..>>
> > > In 1st case the Filter wont get into action at all unless the scan flow>> > > > sees a valid cell. The delete processing happens as 1st step before the>>
> > > filter processinf step happening.>>
> > >>
> > > In this case I am wondering why you can not add the specific 1st>
> > qualifier>>
> > > in the get part itself along with the column range filter. I mean>>
> > >>
> > > get 'mytable', 'MY_ROW', {COLUMN=>['pcf: *1499000 * '],>>
> > > FILTER=>ColumnRangeFilter.new(Bytes.toBytes(1499000.to_java(:int)),>>
> > > true, Bytes.toBytes(1499010.to_java(:int)), false)}>>
> > >>
> > > Pardon the syntax it might not be proper for the shell.. Can this be>
> > done?>>
> > > This will make the scan to make a seek to the given qualifier at 1st>
> > step>>
> > > itself.>>
> > >>
> > > Anoop>>
> > >>
> > > On Thu, Sep 12, 2019 at 10:18 PM Udai Bhan Kashyap (BLOOMBERG/>
> > PRINCETON) <>>
> > > [email protected]> wrote:>>
> > >>
> > > > Are you keeping the deleted cells? Check 'VERSIONS' for the column>
> > family>>
> > > > and set it to 1 if you don't want to keep the deleted cells.>>
> > > >>>
> > > > From: [email protected] At: 09/12/19 12:40:01To:>>
> > > > [email protected]>>
> > > > Subject: Re: HBase Scan consumes high cpu>>
> > > >>>
> > > > Hi,>>
> > > >>>
> > > > As said earlier, we have populated the rowkey "MY_ROW" with integers>>
> > > > from 0 to 1500000 as column qualifiers. Then we have deleted the>>
> > > > qualifiers from 0 to 1499000.>>
> > > >>>
> > > > We executed the following query. It took 15.3750 seconds to execute.>>
> > > >>>
> > > > hbase(main):057:0> get 'mytable', 'MY_ROW', {COLUMN=>['pcf'],>>
> > > > FILTER=>ColumnRangeFilter.new(Bytes.toBytes(1499000.to_java(:int)),>>
> > > > true, Bytes.toBytes(1499010.to_java(:int)), false)}>>
> > > > COLUMN CELL>>
> > > > pcf:\x00\x16\xDFx timestamp=1568123881899,>>
> > > > value=\x00\x16\xDFx>>
> > > > pcf:\x00\x16\xDFy timestamp=1568123881899,>>
> > > > value=\x00\x16\xDFy>>
> > > > pcf:\x00\x16\xDFz timestamp=1568123881899,>>
> > > > value=\x00\x16\xDFz>>
> > > > pcf:\x00\x16\xDF{ timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF{>>
> > > > pcf:\x00\x16\xDF| timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF|>>
> > > > pcf:\x00\x16\xDF} timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF}>>
> > > > pcf:\x00\x16\xDF~ timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF~>>
> > > > pcf:\x00\x16\xDF\x7F timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF\x7F>>
> > > > pcf:\x00\x16\xDF\x80 timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF\x80>>
> > > > pcf:\x00\x16\xDF\x81 timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF\x81>>
> > > > 1 row(s) in 15.3750 seconds>>
> > > >>>
> > > >>>
> > > > Now we inserted a new column with qualifier 10 (\x0A), such that it>>
> > > > comes earlier in lexicographical order. Now we executed the same>
> > query.>>
> > > > It only took 0.0240 seconds.>>
> > > >>>
> > > > hbase(main):058:0> put 'mytable', 'MY_ROW', "pcf:\x0A", "\x00">>
> > > > 0 row(s) in 0.0150 seconds>>
> > > > hbase(main):059:0> get 'mytable', 'MY_ROW', {COLUMN=>['pcf'],>>
> > > > FILTER=>ColumnRangeFilter.new(Bytes.toBytes(1499000.to_java(:int)),>>
> > > > true, Bytes.toBytes(1499010.to_java(:int)), false)}>>
> > > > COLUMN CELL>>
> > > > pcf:\x00\x16\xDFx timestamp=1568123881899,>>
> > > > value=\x00\x16\xDFx>>
> > > > pcf:\x00\x16\xDFy timestamp=1568123881899,>>
> > > > value=\x00\x16\xDFy>>
> > > > pcf:\x00\x16\xDFz timestamp=1568123881899,>>
> > > > value=\x00\x16\xDFz>>
> > > > pcf:\x00\x16\xDF{ timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF{>>
> > > > pcf:\x00\x16\xDF| timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF|>>
> > > > pcf:\x00\x16\xDF} timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF}>>
> > > > pcf:\x00\x16\xDF~ timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF~>>
> > > > pcf:\x00\x16\xDF\x7F timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF\x7F>>
> > > > pcf:\x00\x16\xDF\x80 timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF\x80>>
> > > > pcf:\x00\x16\xDF\x81 timestamp=1568123881899,>>
> > > > value=\x00\x16\xDF\x81>>
> > > > 1 row(s) in 0.0240 seconds>>
> > > > hbase(main):060:0>>>
> > > >>>
> > > >>>
> > > > We were able to reproduce the result consistently same, the pattern>>
> > > > being bulk insert followed by bulk delete of most of the earlier>
> > columns.>>
> > > >>>
> > > >>>
> > > > We observed the following behaviour while debugging the StoreScanner>>
> > > > (regionserver).>>
> > > >>>
> > > > Case 1:>>
> > > >>>
> > > > 1. When StoreScanner.next() is called, it starts to iterate over the>>
> > > > cells from the start of the rowkey.>>
> > > >>>
> > > > 2. As all the cells are deleted (from 0 to 1499000), we could see>>
> > > > alternate delete and put type cells. Now, the>>
> > > > NormalUserScanQueryMatcher.match() returns>>
> > > > ScanQueryMatcher.MatchCode.SKIP and>>
> > > > ScanQueryMatcher.MatchCode.SEEK_NEXT_COL for Delete and Put type cell>>
> > > > respectively. This iteration happens throughout the range of 0 to>
> > 1499000.>>
> > > >>>
> > > > 3. This happens until a valid Put type cell is encountered, where the>>
> > > > matcher applies the ColumnRangeFilter to the cell, which in turm>
> > returns>>
> > > > ScanQueryMatcher.MatchCode.SEEK_NEXT_USING_HINT. In the next>
> > iteration>>
> > > > it seeks directly to the desired column.>>
> > > >>>
> > > >>>
> > > > Case 2:>>
> > > >>>
> > > > 1. When StoreScanner.next() is called, it starts to iterate over the>>
> > > > cells from the start of the rowkey.>>
> > > >>>
> > > > 2. When the Put cell of qualifier 10 (\x0A) is encountered, the>
> > matcher>>
> > > > returns ScanQueryMatcher.MatchCode.SEEK_NEXT_USING_HINT. In the next>>
> > > > iteration it seeks directly to the desired column.>>
> > > >>>
> > > >>>
> > > > Please let us know if this behaviour is intentional or it could be>
> > avoided.>>
> > > >>>
> > > > Regards,>>
> > > >>>
> > > > Solvannan R M>>
> > > >>>
> > > >>>
> > > > On 2019/09/10 17:12:36, Josh Elser wrote:>>
> > > > > Deletes are held in memory. They represent data you have to>
> > traverse >>>
> > > > > until that data is flushed out to disk. When you write a new cell>>
> > > > with a >>>
> > > > > qualifier of 10, that sorts, lexicographically, "early" with>
> > respect>>
> > > > to >>>
> > > > > the other qualifiers you've written.>>>
> > > > >>>
> > > > > By that measure, if you are only scanning for the first column in>
> > this >>>
> > > > > row which you've loaded with deletes, it would make total sense>
> > to me >>>
> > > > > that the first case is slow and the second fast is fast>>>
> > > > >>>
> > > > > Can you please share exactly how you execute your "query" for>>
> > > > both(all) >>>
> > > > > scenarios?>>>
> > > > >>>
> > > > > On 9/10/19 11:35 AM, Solvannan R M wrote:>>>
> > > > > > Hi,>>>
> > > > > > >>>
> > > > > > We have been using HBase (1.4.9) for a case where timeseries data>> > > > > is continuously inserted and deleted (high churn) against a single>>
> > > > rowkey. The column keys would represent timestamp more or less.>
> > When we>>
> > > > scan this data using ColumnRangeFilter for a recent time-range,>
> > scanner>>
> > > > for the stores (memstore & storefiles) has to go through contiguous>> > > > > deletes, before it reaches the requested timerange data. While using>>
> > > > this scan, we could notice 100% cpu usages in single core by the>>
> > > > regionserver process.>>>
> > > > > > >>>
> > > > > > So, for our case, most of the cells with older timestamps will be>>
> > > > in deleted state. While traversing these deleted cells, the>
> > regionserver>>
> > > > process causing 100% cpu usage in single core.>>>
> > > > > > >>>
> > > > > > We tried to trace the code for scan and we observed the following>>
> > > > behaviour.>>>
> > > > > > >>>
> > > > > > 1. While scanner is initialized, it seeked all the store-scanners>>
> > > > to the start of the rowkey.>>>
> > > > > > 2. Then it traverses the deleted cells and discards it (as it was>>
> > > > deleted) one by one.>>>
> > > > > > 3. When it encounters a valid cell (put type), it applies the>>
> > > > filter and it returns SEEK_TO_NEXT_USING_HINT.>>>
> > > > > > 4. Now the scanner seeks to the required key directly and>
> > returning>>
> > > > the results quickly then.>>>
> > > > > > >>>
> > > > > > For confirming the mentioned behaviour, we have done a test:>>> > > > > > > 1. We have populated a single rowkey with column qualifier as a>>
> > > > range of integers of 0 to 1500000 with random data.>>>
> > > > > > 2. We then deleted the column qualifier range of 0 to 1499000.>>>
> > > > > > 3. Now the data is only in memsore. No store file exists.>>>
> > > > > > 4. Now we scanned the rowkey with ColumnRangeFilter[1499000,>>
> > > > 1499010).>>>
> > > > > > 5. The query took 12 seconds to execute. During this query, a>>
> > > > single core is completely used>>>
> > > > > > 6. Then we put a new cell with qualifier 10.>>>
> > > > > > 7. Executed the same query, it took 0.018 seconds to execute.>>>
> > > > > > >>>
> > > > > > Kindly check this and advise !.>>>
> > > > > > >>>
> > > > > > Regards,>>>
> > > > > > Solvannan R M>>>
> > > > > > >>>
> > > > >>>
> > > >>>
> > > >>>
> > > >>>
> > >>
> >>
>

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