From 13bb3cbfbb0b413144a126604afea8437457b8bc Mon Sep 17 00:00:00 2001 From: moustafaalaa Date: Tue, 3 Oct 2023 23:50:48 +0100 Subject: [PATCH] [ADD] Hive comparison --- Ch03-HadoopMR/Ch03-HadoopMR.tex | 57 +++++++++++++++++++++++++++++++- main.pdf | Bin 424635 -> 430191 bytes preamble/preamble.tex | 3 ++ preamble/presentation-mode.tex | 2 +- 4 files changed, 60 insertions(+), 2 deletions(-) diff --git a/Ch03-HadoopMR/Ch03-HadoopMR.tex b/Ch03-HadoopMR/Ch03-HadoopMR.tex index d401454..faf271b 100644 --- a/Ch03-HadoopMR/Ch03-HadoopMR.tex +++ b/Ch03-HadoopMR/Ch03-HadoopMR.tex @@ -83,6 +83,61 @@ \subsubsection{Overview of Apache Hive} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +\subsubsection{Comparing Hive to Traditional Databases} +\begin{frame}{Comparison between Apache Hive and Traditional RDBMS (Part 1)} + \begin{table}[h!] + \centering + \resizebox{\textwidth}{!}{% + \begin{tabular}{|m{5cm}|m{6cm}|m{6cm}|} + \hline + \rowcolor{Gray} + \textbf{Feature} & \textbf{Apache Hive} & \textbf{Traditional RDBMS} \\ + \hline + Purpose & Big data analytics. & Transactional systems and traditional data warehousing. \\ + \hline + Query Language & HiveQL, similar to SQL. & SQL. \\ + \hline + Speed & Slower, optimized for batch processing. & Faster, optimized for real-time transactional processing. \\ + \hline + Data Size & Designed to handle petabytes of data. & gigabytes to terabytes; some systems can handle petabytes at higher cost. \\ + \hline + ACID Properties & Limited ACID support. & Full ACID support. \\ + \hline + \end{tabular} + } + \caption{Comparison between Apache Hive and Traditional RDBMS} + \end{table} + \end{frame} + + \begin{frame}{Comparison between Apache Hive and Traditional RDBMS (Part 2)} + \begin{table}[h!] + \centering + \resizebox{\textwidth}{!}{% + \begin{tabular}{|m{5cm}|m{6cm}|m{6cm}|} + \hline + \rowcolor{Gray} + \textbf{Feature} & \textbf{Apache Hive} & \textbf{Traditional RDBMS} \\ + \hline + Storage & Built on HDFS. & Uses internal storage mechanisms. \\ + \hline + Metadata Storage & Stored in Hive Metastore. & Stored in system catalogs within the database. \\ + \hline + Compute Engine & MapReduce, Tez, or Spark can be used. & Built-in engine, tightly integrated. \\ + \hline + Query Execution Location & Executes on Hadoop cluster nodes. & Executes on the database server. \\ + \hline + Data Storage Formats & ORC, Parquet, CSV, JSON, XML, Avro & Proprietary Binary Format \\ + \hline + Max Simultaneous Connections & Governed by Hadoop Cluster & Varies (Hundreds to Thousands) \\ + \hline + \end{tabular} + } + \caption{Comparison between Apache Hive and Traditional RDBMS} + \end{table} + \end{frame} + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + \subsection{Hive Architecture} \begin{frame}{Abstract Components of Apache Hive} @@ -91,7 +146,7 @@ \subsection{Hive Architecture} \item Hive Services. \item Hive Metadata (Metastore). \item Storage. - \item Computing. + \item Compute. \end{itemize} \end{frame} 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