Detailed Analysis of the F1 Distributed SQL Database System: Report

This report provides a comprehensive analysis of the F1 distributed SQL database system, originally developed by Google to support its AdWords business. The report delves into the architecture of F1, highlighting its hybrid nature that combines the high availability and scalability of NoSQL systems with the consistency and usability of traditional SQL databases. It examines the key design goals of F1, including scalability, availability, usability, and consistency. The report explores the research methodologies used, including qualitative research design and secondary data collection from journal articles and online sources. The findings emphasize the benefits of F1, such as enhanced scalability, consistency, and the use of optimistic transactions. Furthermore, the report highlights the issues addressed by the author, such as the challenge of synchronous replication and the limitations of traditional MySQL systems. In conclusion, the report underscores the significance of F1 in improving system scalability and reliability, offering insights into its architecture, design, and potential for future research involving primary data analysis techniques.

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Data Base system

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Table of Contents
Introduction...........................................................................................................................................2
Intention and content of the journal.....................................................................................................2
Research methods.................................................................................................................................3
Research design.................................................................................................................................3
Research strategy..............................................................................................................................3
Data collection method.....................................................................................................................4
Data analysis......................................................................................................................................4
Findings.................................................................................................................................................4
Issues highlighted by the author...........................................................................................................4
The conclusion of the journal................................................................................................................5
Conclusion.............................................................................................................................................5
References.............................................................................................................................................6

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Introduction
F1 is the distributed relational database scheme which is generated and produced at
Google to support the Ad-Words business. It is observed that F1 is a hybrid database
system which combines the high availability, large scalability and the consistency of the
current SQL databases. The aim of this report is to gather information about the SQL
database system and the basic architecture of the F1 system. In which a journal paper
will be discussed which is completely based on the F1 database system. This study is
cauterised into major four portions like purpose and content of the journal article,
research methodologies, finding and issues emphasized by the author.
Intention and content of the journal
The title of the article is “F1: A Distributed SQL Database That Scales” which was written
by Jeff Shute, Radek, Vingralek, Bart Samwel, and Ben Handy. According to the
researcher the F1 database is built on the spanner that provides the synchronous cross
replication and better consistency (Shute, et al., 2013). The author analyzed that the
synchronous replication implies higher commit latency which can be resolved with the
help of the hierarchical schema model. Such kind of database system involves a
dispersed SQL query machine and unconscious alteration tracing system in their
process. According to the author, F1 is defined as the fault-tolerant distributed OLTP
and OLAP database system which is built and developed at Google as the latest storage
system. This kind of technique was designed and implemented to replace the sharded
MySQL which was not able to meet the requirements of the individuals (Baker, et al.,
2011). There are main four goals and objectives of the F1 designs such as availability,
usability, scalability, and consistency which are described in this study. Recent
investigation observed that all these design goals are mutually exclusive and the aim of
this journal paper is to indicate how individuals achieved all of these goals in the F1
database system (Rae, et al., 2013). The F1 comes from genetics where a familial 1
hybrid is the initial generation of the MySQL database and F1 system is built on the top
of spanner that has potential to increase the scalability of the data storage and ordering
properties (Das, Agrawal, and El Abbadi, 2013). In this modern era, there are many
featured added from spanners such as distributed SQL queries, transitionally consistent,
optimistic transactions and automatic change history publishing and recording. The

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researcher also analyzed that the F1 servers can interconnect with spanner networks
outside their own database and it cannot be communicated with the remote CFS
instances. The main advantage of this system is that it allows consumers to interconnect
with the various F1 servers for every request. The main problem of this system is that
when a consumer uses pessimistic transactions and it must hold locks (Fotache, and
Strimbei, 2015). In the F1 system, the consumers and individuals communicate with the
F1 by using client library and other tools such as ad-hoc SQL can be designed with the
help of client library. In which the consumer transfer requests too many F1 servers that
are responsible for reading and writing the data or information from the remote data
resources. Researcher provided the fundamental concept of the F1 with their
architecture diagram and it also explained the data modeling technologies used in the
F1 database systems (Lawrence, 2014).
Research methods
The research mythologies involved the different types of investigation plans, strategies,
and methods that are used by the researcher at the time of the investigation.
Approaches, data collection methods, and data analysis all these are used by the
researcher to enhance the effectiveness of the research (Shute, et al., 2012). This section
will describe the various kinds of research methodologies used by the investigator and
data analysis techniques.
Research design
In this study, the qualitative design is used that delivers the hypothetical material about
the topic. In which the info is composed and obtained from the previous investigation,
persons and specialists to understand and analyze their opinions on the F1 database
system. The relevant data or information is gathered with the help of a literature
review, previous investigation, online and offline sources, and books.
Research strategy
In this research paper, the author provided only theoretical information about the F1
database with their architecture which helps readers to gain their knowledge and skills.
Such kind of research design is used to obtain the first hand and related information
about F1 database technology. With the help of a literature review the researcher
understands the phenomena of the F1 database and SQL process in the system.

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Data collection method
Only secondary types of data are collected in this investigation because the researcher
did not involve any survey or case study to gather the primary data. The secondary data
is collected and obtained from many sources, for example, journal paper, recent
investigation, websites, online websites, and books (Shute, et al., 2013). By using this
technique the research scholar is able to enhance the effectiveness of the paper and
gained an effective conclusion at the end of the investigation.
Data analysis
The data analysis approach is adopted by the investigator to evaluate the secondary
data or information that can help them to collect the relevant information about F1
database system. In this modern ear, there are numerous kinds of analysis techniques
developed such as content analysis, disclosure analysis, and statistical analysis. In this
journal article, content analysis technique is used to determine the reason for the
implementation and development of F1 database. With the help of all these research
methodologies investigator has increased the efficiency of their paper and achieved the
objectives of this study.
Findings
From this journal paper, it is founded that many developers spend their times for
building and developing complex techniques and methods to cope with the eventual
consistency and control data which may be out of date. This journal article observed
that F1 is one of the advanced hybrid systems that have the ability to enhance the
scalability, consistency, and efficiency of the SQL database system. Many consumers and
clients of the F1 systems used the optimistic transaction because of their several
advantages such as tolerating misbehaved consumers, ling lasting transaction, and
server-side reliability.
Issues highlighted by the author
According to the author, F1 is built on the spanner that provides synchronous cross-
database replication and better consistency. Research observed that the process of
synchronous replication implies the large commit latency which is one of the common
problems occurs in the F1 system. The traditional MySQL is not able to meet the

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requirements of the clients and they do not provide the scalability and reliability of the
system these issues were highlighted by the author.
The conclusion of the journal
This journal paper is completely based on the F1 database system and the author
explained the concept of the F1 system with their goals. The researcher also described
the basic architecture of the F1 technique and evaluates their data models.
Conclusion
This report analyzed the significance of the F1 system in for improving the scalability
and reliability of the system. In which the intention and content of the journal also
explained to understand the phenomena of the F1 system which help to reduce the
research gaps in the previous investigation. There are many research methodologies
also discussed in this report and in future researcher will involve primary data analysis
technique to improve the effectiveness of the investigation.

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References
Baker, J., Bond, C., Corbett, J.C., Furman, J.J., Khorlin, A., Larson, J., Leon, J.M., Li, Y., Lloyd,
A. and Yushprakh, V., (2011) Megastore: Providing scalable, highly available storage for
interactive services. In CIDR, 11(2), pp. 223-234.
Das, S., Agrawal, D., and El Abbadi, A., (2013) Elastras: An elastic, scalable, and self-
managing transactional database for the cloud. ACM Transactions on Database Systems
(TODS), 38(1), p.5.
Fotache, M. and Strimbei, C., (2015) SQL and data analysis. Some implications for data
analysis and higher education. Procedia Economics and Finance, 20(2), pp.243-251.
Lawrence, R., (2014) Integration and virtualization of relational SQL and NoSQL systems
including MySQL and MongoDB. In Computational Science and Computational
Intelligence (CSCI), 2014 International Conference on, 1(2), pp. 285-290.
Rae, I., Rollins, E., Shute, J., Sodhi, S. and Vingralek, R., (2013) Online, asynchronous
schema change in F1. Proceedings of the VLDB Endowment, 6(11), pp.1045-1056.
Shute, J., Oancea, M., Ellner, S., Handy, B., Rollins, E., Samwel, B., Vingralek, R., Whipkey,
C., Chen, X., Jegerlehner, B. and Littlefield, K., (2012) F1: the fault-tolerant distributed
RDBMS supporting google's ad business. In Proceedings of the 2012 ACM SIGMOD
International Conference on Management of Data, 12(2), pp. 777-778.
Shute, J., Vingralek, R., Samwel, B., Handy, B., Whipkey, C., Rollins, E., Oancea, M.,
Littlefield, K., Menestrina, D., Ellner, S. and Cieslewicz, J., (2013) F1: A distributed SQL
database that scales. Proceedings of the VLDB Endowment, 6(11), pp.1068-1079.