Thank you so much for the clarification Kevin.
Regards,
Mohammad Tariq
On Thu, Dec 13, 2012 at 9:00 PM, Kevin O'dell <[email protected]>wrote:
> Mohammad,
>
> I am not sure you are thinking about Impala correctly. It still uses
> HDFS so your data increasing over time is fine. You are not going to need
> to tune for special CPU, Storage, or Network. Typically with Impala you
> are going to be bound at the disks as it functions off of data locality.
> You can also use compression of Snappy, GZip, and BZip to help with the
> amount of data you are storing. You will not need to frequently update
> your hardware.
>
> On Thu, Dec 13, 2012 at 10:06 AM, Mohammad Tariq <[email protected]>
> wrote:
>
> > Oh yes..Impala..good point by Kevin.
> >
> > Kevin : Would it be appropriate if I say that I should go for Impala if
> my
> > data is not going to increase dramatically over time or if I have to work
> > on only a subset of my BigData?Since Impala uses MPP, it may
> > require specialized hardware tuned for CPU, storage and network
> performance
> > for better results, which could become a problem if have to upgrade the
> > hardware frequently because of the growing data.
> >
> > Regards,
> > Mohammad Tariq
> >
> >
> >
> > On Thu, Dec 13, 2012 at 8:17 PM, Kevin O'dell <[email protected]
> > >wrote:
> >
> > > To Mohammad's point. You can use HBase for quick scans of the data.
> > Hive
> > > for your longer running jobs. Impala over the two for quick adhoc
> > > searches.
> > >
> > > On Thu, Dec 13, 2012 at 9:44 AM, Mohammad Tariq <[email protected]>
> > > wrote:
> > >
> > > > I am not saying Hbase is not good. My point was to consider Hive as
> > well.
> > > > Think about the approach keeping both the tools in mind and decide. I
> > > just
> > > > provided an option keeping in mind the available built-in Hive
> > features.
> > > I
> > > > would like to add one more point here, you can map your Hbase tables
> to
> > > > Hive.
> > > >
> > > > Regards,
> > > > Mohammad Tariq
> > > >
> > > >
> > > >
> > > > On Thu, Dec 13, 2012 at 7:58 PM, bigdata <[email protected]>
> > > wrote:
> > > >
> > > > > Hi, Tariq
> > > > > Thanks for your feedback. Actually, now we have two ways to reach
> the
> > > > > target, by Hive and by HBase.Could you tell me why HBase is not
> good
> > > for
> > > > > my requirements?Or what's the problem in my solution?
> > > > > Thanks.
> > > > >
> > > > > > From: [email protected]
> > > > > > Date: Thu, 13 Dec 2012 15:43:25 +0530
> > > > > > Subject: Re: How to design a data warehouse in HBase?
> > > > > > To: [email protected]
> > > > > >
> > > > > > Both have got different purposes. Normally people say that Hive
> is
> > > > slow,
> > > > > > that's just because it uses MapReduce under the hood. And i'm
> sure
> > > that
> > > > > if
> > > > > > the data stored in HBase is very huge, nobody would write
> > sequential
> > > > > > programs for Get or Scan. Instead they will write MP jobs or do
> > > > something
> > > > > > similar.
> > > > > >
> > > > > > My point is that nothing can be 100% real time. Is that what you
> > > > want?If
> > > > > > that is the case I would never suggest Hadoop on the first place
> as
> > > > it's
> > > > > a
> > > > > > batch processing system and cannot be used like an OLTP system,
> > > unless
> > > > > you
> > > > > > have thought of some additional stuff. Since you are talking
> about
> > > > > > warehouse, I am assuming you are going to store and process
> > gigantic
> > > > > > amounts of data. That's the only reason I had suggested Hive.
> > > > > >
> > > > > > The whole point is that everything is not a solution for
> > everything.
> > > > One
> > > > > > size doesn't fit all. First, we need to analyze our particular
> use
> > > > case.
> > > > > > The person, who says Hive is slow, might be correct. But only for
> > his
> > > > > > scenario.
> > > > > >
> > > > > > HTH
> > > > > >
> > > > > > Regards,
> > > > > > Mohammad Tariq
> > > > > >
> > > > > >
> > > > > >
> > > > > > On Thu, Dec 13, 2012 at 3:17 PM, bigdata <
> [email protected]>
> > > > > wrote:
> > > > > >
> > > > > > > Hi,
> > > > > > > I've got the information that HIVE 's performance is too low.
> It
> > > > access
> > > > > > > HDFS files and scan all data to search one record. IS it TRUE?
> > And
> > > > > HBase is
> > > > > > > much faster than it.
> > > > > > >
> > > > > > >
> > > > > > > > From: [email protected]
> > > > > > > > Date: Thu, 13 Dec 2012 15:12:25 +0530
> > > > > > > > Subject: Re: How to design a data warehouse in HBase?
> > > > > > > > To: [email protected]
> > > > > > > >
> > > > > > > > Hi there,
> > > > > > > >
> > > > > > > > If you are really planning for a warehousing solution
> then I
> > > > would
> > > > > > > > suggest you to have a look over Apache Hive. It provides you
> > > > > warehousing
> > > > > > > > capabilities on top of a Hadoop cluster. Along with that it
> > also
> > > > > provides
> > > > > > > > an SQLish interface to the data stored in your warehouse,
> which
> > > > > would be
> > > > > > > > very helpful to you, in case you are coming from an SQL
> > > background.
> > > > > > > >
> > > > > > > > HTH
> > > > > > > >
> > > > > > > >
> > > > > > > >
> > > > > > > > Regards,
> > > > > > > > Mohammad Tariq
> > > > > > > >
> > > > > > > >
> > > > > > > >
> > > > > > > > On Thu, Dec 13, 2012 at 2:43 PM, bigdata <
> > > [email protected]>
> > > > > > > wrote:
> > > > > > > >
> > > > > > > > > Thanks. I think a real example is better for me to
> understand
> > > > your
> > > > > > > > > suggestions.
> > > > > > > > > Now I have a relational table:ID LoginTime
> > > > > > > DeviceID1
> > > > > > > > > 2012-12-12 12:12:12 abcdef2 2012-12-12 19:12:12
> > > > > abcdef3
> > > > > > > > > 2012-12-13 10:10:10 defdaf
> > > > > > > > > There are several requirements about this table:1. How many
> > > > device
> > > > > > > login
> > > > > > > > > in each day?1. For one day, how many new device login?
> (never
> > > > login
> > > > > > > > > before)1. For one day, how many accumulated device login?
> > > > > > > > > How can I design HBase tables to calculate these data?Now
> my
> > > > > solution
> > > > > > > > > is:table A:
> > > > > > > > > rowkey: date-deviceidcolumn family: logincolumn qualifier:
> > > > > 2012-12-12
> > > > > > > > > 12:12:12/2012-12-12 19:12:12....
> > > > > > > > > table B:rowkey: deviceidcolumn family:null or anyvalue
> > > > > > > > >
> > > > > > > > > For req#1, I can scan table A and use prefixfilter(rowkey)
> to
> > > > > check one
> > > > > > > > > special date, and get records countFor req#2, I get table b
> > > with
> > > > > each
> > > > > > > > > deviceid, and count result
> > > > > > > > > For req#3, count table A with prefixfilter like 1.
> > > > > > > > > Does it OK? Or other better solutions?
> > > > > > > > > Thanks!!
> > > > > > > > >
> > > > > > > > > > CC: [email protected]
> > > > > > > > > > From: [email protected]
> > > > > > > > > > Subject: Re: How to design a data warehouse in HBase?
> > > > > > > > > > Date: Thu, 13 Dec 2012 08:43:31 +0000
> > > > > > > > > > To: [email protected]
> > > > > > > > > >
> > > > > > > > > > You need to spend a bit of time on Schema design.
> > > > > > > > > > You need to flatten your Schema...
> > > > > > > > > > Implement some secondary indexing to improve join
> > > > performance...
> > > > > > > > > >
> > > > > > > > > > Depends on what you want to do... There are other options
> > > > too...
> > > > > > > > > >
> > > > > > > > > > Sent from a remote device. Please excuse any typos...
> > > > > > > > > >
> > > > > > > > > > Mike Segel
> > > > > > > > > >
> > > > > > > > > > On Dec 13, 2012, at 7:09 AM, lars hofhansl <
> > > > [email protected]>
> > > > > > > wrote:
> > > > > > > > > >
> > > > > > > > > > > For OLAP type queries you will generally be better off
> > > with a
> > > > > truly
> > > > > > > > > column oriented database.
> > > > > > > > > > > You can probably shoehorn HBase into this, but it
> wasn't
> > > > really
> > > > > > > > > designed with raw scan performance along single columns in
> > > mind.
> > > > > > > > > > >
> > > > > > > > > > >
> > > > > > > > > > >
> > > > > > > > > > > ________________________________
> > > > > > > > > > > From: bigdata <[email protected]>
> > > > > > > > > > > To: "[email protected]" <[email protected]>
> > > > > > > > > > > Sent: Wednesday, December 12, 2012 9:57 PM
> > > > > > > > > > > Subject: How to design a data warehouse in HBase?
> > > > > > > > > > >
> > > > > > > > > > > Dear all,
> > > > > > > > > > > We have a traditional star-model data warehouse in
> RDBMS,
> > > now
> > > > > we
> > > > > > > want
> > > > > > > > > to transfer it to HBase. After study HBase, I learn that
> > HBase
> > > is
> > > > > > > normally
> > > > > > > > > can be query by rowkey.
> > > > > > > > > > > 1.full rowkey (fastest)2.rowkey filter (fast)3.column
> > > > > > > family/qualifier
> > > > > > > > > filter (slow)
> > > > > > > > > > > How can I design the HBase tables to implement the
> > > warehouse
> > > > > > > > > functions, like:1.Query by DimensionA2.Query by DimensionA
> > and
> > > > > > > > > DimensionB3.Sum, count, distinct ...
> > > > > > > > > > > From my opinion, I should create several HBase tables
> > with
> > > > all
> > > > > > > > > combinations of different dimensions as the rowkey. This
> > > solution
> > > > > will
> > > > > > > lead
> > > > > > > > > to huge data duplication. Is there any good suggestions to
> > > solve
> > > > > it?
> > > > > > > > > > > Thanks a lot!
> > > > > > > > >
> > > > > > > > >
> > > > > > >
> > > > > > >
> > > > >
> > > > >
> > > >
> > >
> > >
> > >
> > > --
> > > Kevin O'Dell
> > > Customer Operations Engineer, Cloudera
> > >
> >
>
>
>
> --
> Kevin O'Dell
> Customer Operations Engineer, Cloudera
>
