contains 500 fields (separated by pipe)
>>> and each of this fields is particularly important.
>>>
>>> Cassandra will not manage that since you will need 500 indexes. HDFS is
>>> the proper way.
>>>
>>>
>>>
>>>
>>>
>>
d 500 indexes. HDFS is
>> the proper way.
>>
>>
>>
>>
>>
>> *From:* Welly Tambunan [mailto:if05...@gmail.com]
>> *Sent:* 23 October 2016 10:19
>> *To:* user@cassandra.apache.org
>> *Subject:* Re: Hadoop vs Cassandra
>>
>>
>&g
ll need 500 indexes. HDFS is
> the proper way.
>
>
>
>
>
> *From:* Welly Tambunan [mailto:if05...@gmail.com]
> *Sent:* 23 October 2016 10:19
> *To:* user@cassandra.apache.org
> *Subject:* Re: Hadoop vs Cassandra
>
>
>
> I like muti data centre resillience in cass
is particularly important.
Cassandra will not manage that since you will need 500 indexes. HDFS is the
proper way.
From: Welly Tambunan [mailto:if05...@gmail.com]
Sent: 23 October 2016 10:19
To: user@cassandra.apache.org
Subject: Re: Hadoop vs Cassandra
I like muti data centre resillience in cassandra.
I
"from a particular query" should be " from a particular country"
On Sun, Oct 23, 2016 at 2:36 PM, Ali Akhtar wrote:
> They can be, but I would assume that if your Cassandra data model is
> inefficient for the kind of queries you want to do, Spark won't magically
> take
They can be, but I would assume that if your Cassandra data model is
inefficient for the kind of queries you want to do, Spark won't magically
take that way.
For example, say you have a users table. Each user has a country, which
isn't a partitioning key or clustering key.
If you wanted to
I like muti data centre resillience in cassandra.
I think thats plus one for cassandra.
Ali, complex analytics can be done in spark right?
On 23 Oct 2016 4:08 p.m., "Ali Akhtar" wrote:
>
> I would say it depends on your use case.
>
> If you need a lot of queries that
I would say it depends on your use case.
If you need a lot of queries that require joins, or complex analytics of
the kind that Cassandra isn't suited for, then HDFS / HBase may be better.
If you can work with the cassandra way of doing things (creating new tables
for each query you'll need to
It’s reasonably common to use Cassandra to cover both online and analytics
requirements, particularly using it in conjunction with Spark. You can use
Cassandra’s multi-DC functionality to have online and analytics DCs for a
reasonable degree of workload separation without having to build ETL (or
I mean. HDFS and HBase.
On Sun, Oct 23, 2016 at 4:00 PM, Ali Akhtar wrote:
> By Hadoop do you mean HDFS?
>
>
>
> On Sun, Oct 23, 2016 at 1:56 PM, Welly Tambunan wrote:
>
>> Hi All,
>>
>> I read the following comparison between hadoop and cassandra.
By Hadoop do you mean HDFS?
On Sun, Oct 23, 2016 at 1:56 PM, Welly Tambunan wrote:
> Hi All,
>
> I read the following comparison between hadoop and cassandra. Seems the
> conclusion that we use hadoop for data lake ( cold data ) and Cassandra for
> hot data (real time
Hi All,
I read the following comparison between hadoop and cassandra. Seems the
conclusion that we use hadoop for data lake ( cold data ) and Cassandra for
hot data (real time data).
http://www.datastax.com/nosql-databases/nosql-cassandra-and-hadoop
My question is, can we just use cassandra to
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