lifecycle)  2012-2018 IBM Research – Almaden, USA  Declarative large-scale machine learning  Optimizer and runtime of Apache SystemML  2011 PhD TU Dresden, Germany  Cost-based optimization of integration integration flows  Systems support for time series forecasting  In-memory indexing and query processing Data Management Group DB group https://github.com/ apache/systemds 6 706.015 Introduction to Romulo Goncalves: An architecture for recycling intermediates in a column-store. SIGMOD 2009  Raw Query Processing  #8.1 Dominik Durner, Viktor Leis, Thomas Neumann: JSON Tiles: Fast Analytics on Semi-

only allowed between assignments. GOOD: PredictCTR <- function(query, property, num.days, show.plot = TRUE) BAD: PredictCTR <- function(query, property, num.days, show.plot = TRUE) Ideally, unit tests

is introduced. Later, Raman and Swart investigated query processing on heavyweight Huffman coding schemes [40], Later, [40] investigated query processing on heavyweight Huffman coding schemes, 22

TPC-DS, JOB, MLPerf  #4 End-to-end Applications  Evaluate in larger scope of real datasets and query workloads  Examples: Customer workload, ML pipelines (dataprep, training, eval) Experiments and agreed benchmarks  Benchmarks can define a field and foster innovation  #1 Data Management  Query processing: 007, TPC-C, TPC-E, TPC-H, TPC-DS (w/ audit)  Join ordering: JOB  #2 “Big Data”

Type Information (RTTI) Avoid using Run Time Type Information (RTTI). RTTI allows a programmer to query the C++ class of an object at run time. This is done by use of typeid or dynamic_cast. Querying the