![]() ![]() to make sure that there are no cache effects or undesired influences between the repeated 3 or more times to ensure the representativeness of the results Configure the Big Data platform under test to address the benchmark scenario. Generate the test data using typically data generator Scale Factor, query type, workload type, ) Install and configure the Big Data Benchmark. Operating System, Network, Programming Frameworks, Install and configure all hardware and software components.The general approach consists of 4 phases:. by using a different columnar file format configuration by changing the columnar file format type or Investigate how the overall performance of an engine (Hive or Parquet is first choice for SparkSQL and ImpalaĬontrary to other studies, we compared ORC and Parquet File Formatsīy executing each file format on the same processing engine! SQL-on-Hadoop Engines + Default File Format ![]() offer a high-level abstraction on top of processing engine (like MapReduce provide SQL-like dialect (called HiveQL) to work with structured data efficiently query data stored in columnar file formats (typically in HDFS) can be used or integrated with any data processing framework or engine take advantage of data encoding and compression strategies open source, general purpose columnar file formats
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