1. Systems and Big Data System

• System is a software that manages resources (computer, memory, storage, network).
  • Compute: computational resources execute code.
  • Memory: memory holds data for active usage.
  • Storage: storage holds long-term data.
  • Network: network provides communication between computers.
• Big Data System manages resources that are specialized (e.g. GPUs) and distributed (cluster of machines).
  • Scale Up: more resources assigned to a single machine.
  • Scale Out: more machines are used on the same task.

2. Compute

• Core: the more cores we have, the more tasks we can run simultaneously.
• Code: high level code to machine code
  • Compiler translates from high level code to machine code.
  • CPU runs an interpeter program that loops over programmer’s code and runs it.
  • Compiler creates Bytecode from high level code and a Virtual Machine (VM) running on the CPU runs the bytecode
• CPU vs. GPU
  • CPUs (few cores that are fast, flexible, independent) are versatile and excel at handling a wide variety of tasks.
  • GPUs (many cores that are slow, float-optimized, coordinated) are specialized for parallel processing and perform exceptionally well in tasks like graphics rendering, scientific simulations, and machine learning when parallelism can be exploited.
• Metric: FLOPS (floating-point operations per second)

3. Memory

• Random Access Memory (RAM):
  • Random: means we can jump around and access data from different locations efficiently. In contrast, some devices that hold data are only efficient sequentially.
  • Byte Addressible: each byte of data has it’s own address the CPU can use to access it; extracting a single bit from a byte actually involves more steps than using the whole byte.
  • Characteristcs: Small, Volatile, Fast.
• Bits and Bytes:
  • N bits can hold 2 possible values.
  • 1 Byte = 8 bits (1 MB/s = 1 Mbps)
  • 1 KB = 1024 Bytes
  • 1 MB = 1024 KB
  • 1 GB = 1024 MB
  • 1 TB = 1024 GB

4. Storage

• Block Devices
  • Hard Disk Drives (HDDs): 0’s/1’s stored on spinning magnetized platter; a moving head reads/writes data.
  • Solid State Disks (SSDs): 0s/1s stored in charged cells; no moving parts (faster).
  • Data is read/written in blocks of many bytes (for example, 0.5 KB), so that reading 1 byte or 1 block takes same time.
  • Characteristics: large, nonvolatile, slow.
• Metric: Capacity (Bytes), Throughput (Bytes/sec), Latency (ms)

5. Network

• When scaling out, many nodes (computers) will be communicating via a network.
• Metric: Latency (sec, ms), Bandwidth/Throughput.

6. Other Terms

• Deployment: running code somewhere.
• Containers: a lightweight alternative to virtual machines.