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A telecommunications company has a substantial amount of data. This data is being created by network elements within their environment.
The company wants to change the way the network elements Call Detail Records (CDR) are stored and analyzed. The existing infrastructure consolidates all of the CDRs into a table structure, and then ingests them into a large database. Once ingested, a query engine accesses the database and performs analysis on these files. The system is functional; however, since the amount of CDRs generated will increase exponentially over the next year, the company is open to alternatives for storing and analyzing these records.
In evaluating alternatives, the key requirements are to reduce cost, the amount of storage, and the amount of time to analyze the data. The customer would like to use Hadoop to analyze the CDRs.
After you have conducted an assessment of the workflow, you have recommended an Isilon Cluster to work within the Hadoop environment.
What would be the best recommendation to the customer for the workflow of Hadoop with Isilon?
When designing Isilon solutions, what issues should you pay special attention to?
What replication option is NOT supported by SyncIQ?
In an Isilon cluster, what is the largest number of nodes that a single file can be striped across?
An existing customer has two NAS systems providing NFS storage in their main datacenter - one is an Isilon cluster and the second is an array from another vendor. Both systems are four years old, and the customer would like to consolidate the storage into a single solution. According to the customer, both systems support identical workloads with similar performance and utilization, and they want the new solution to support 50% performance growth.
Which method can model the workload requirements, and what multiplier will capture the requirements for the new solution?