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From devush <devushan...@gmail.com>
Subject Re: Data format in HBase
Date Fri, 11 Feb 2011 21:12:48 GMT
 I am not sure if it is a good practice to start an old thread?

I just posted the same question, but i already see the response here.

My question at this point is if i have byte array, then how i will see
my row keys? through program only. through shell it is not possible,
we see decimal better, but for program it does not matter.

I might need this in the beginning as we are still doing
coding/debugging. may be later on we will not touch the content
through shell.

How other people are managing the bytes in row keys?

On 26 January 2011 10:45, Friso van Vollenhoven
<fvanvollenhoven@xebia.com> wrote:
> There are indeed a number of toBytes(...) overloads, like Ryan said. When you have a
fixed record type like this, using Bytes.toBytes(...) is likely the simplest and most compact
thing to do. Protobuf and Avro are nice if you have records with optional fields or want to
mix different types of records in one table. Also if you have records that may change over
time (adding fields, etc.).
> Friso
> On 26 jan 2011, at 11:36, Eric wrote:
>> I've been looking at Avro and Protocol Buffers too. I'm storing multiple
>> properties, like a Tweet that has a user id, timestamp, message, etc. I
>> actually thought toBytes() would convert to string and then to bytes (stupid
>> assumtion). I think I´ll convert my Strings to the proper format (int's,
>> longs) and then use toBytes() because protobufs and Avro add too much
>> complexity in this case.
>> 2011/1/26 Friso van Vollenhoven <fvanvollenhoven@xebia.com>
>>> We are using protobuf (http://code.google.com/apis/protocolbuffers/).
>>> That's not by any means a recommendation, just a possibility. What is your
>>> use case?
>>> Friso
>>> On 26 jan 2011, at 10:47, Eric wrote:
>>> I'm wondering what the best way is to store my data in HBase. I'm currently
>>> converting everything to a string and then to a bytes array.
>>> What are others doing? Plain text to to byte arrays and eventually convert
>>> your data back to floats, int, etcetera?

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