Sql tuning guideline

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This document provides guidelines for tuning SQL statements to improve response time. It discusses reviewing table and column statistics, execution plans, and restructuring SQL statements and indexes. Specific techniques covered include gathering statistics, reviewing access paths like index scans and joins, and using SQL profiles to lock optimized plans.

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How wonderful it is that in our modern age, every bit of our biological data can be digitized, stored, and potentially pilfered by cyber thieves! Isn't it just splendid to think that while scientists are busy pushing the boundaries of biotechnology, hackers could be plotting the next big bio-data heist? This delightful scenario is brought to you by the ever-expanding digital landscape of biology and biotechnology, where the integration of computer science, engineering, and data science transforms our understanding and manipulation of biological systems. While the fusion of technology and biology offers immense benefits, it also necessitates a careful consideration of the ethical, security, and associated social implications. But let's be honest, in the grand scheme of things, what's a little risk compared to potential scientific achievements? After all, progress in biotechnology waits for no one, and we're just along for the ride in this thrilling, slightly terrifying, adventure. So, as we continue to navigate this complex landscape, let's not forget the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. After all, what could possibly go wrong? ------------------------- This document provides a comprehensive analysis of the security implications biological data use. The analysis explores various aspects of biological data security, including the vulnerabilities associated with data access, the potential for misuse by state and non-state actors, and the implications for national and transnational security. Key aspects considered include the impact of technological advancements on data security, the role of international policies in data governance, and the strategies for mitigating risks associated with unauthorized data access. This view offers valuable insights for security professionals, policymakers, and industry leaders across various sectors, highlighting the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. The analysis serves as a crucial resource for understanding the complex dynamics at the intersection of biotechnology and security, providing actionable recommendations to enhance biosecurity in an digital and interconnected world. The evolving landscape of biology and biotechnology, significantly influenced by advancements in computer science, engineering, and data science, is reshaping our understanding and manipulation of biological systems. The integration of these disciplines has led to the development of fields such as computational biology and synthetic biology, which utilize computational power and engineering principles to solve complex biological problems and innovate new biotechnological applications. This interdisciplinary approach has not only accelerated research and development but also introduced new capabilities such as gene editing and biomanufact

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Sql tuning guideline

1. SQL Tuning Guideline Sidney · 2011 Feb 16

2. Agenda The Guideline to tune sql Application Logic Table/Column statistics SQL access path SQL join NL or hash Join

3. Response Time The core of user experience

4. Why? So Slow! Application Logic Tune at sql level

5. How to review sql Verifying Optimizer Statistics Reviewing the Execution Plan Restructuring the SQL Statements(code change) Restructuring the Indexes

6. SQLT: Nice tool review top sql Statistics:Tables/Indexes/Columns Execution plan Predication Bind value SQL profile

7. Table/Index stats Table stats Last_Analyzed Num_Rows Sample_Size Index stats Last_Analyzed Num_Rows Sample_Size DISTINCT_KEYS BLEVEL Clustering_Factor

8. Column statistics num_rows num_distinct density num_nulls num_buckets histogram low_value high_value

9. How to gather Table/Column statistics Using auto method exec dbms_stats.gather_table_stats('CS2_PARTY_OWNER','CS2_BKG_RQST',method_opt=>' for all columns size auto', cascade=>true); For specific columns exec dbms_stats.gather_table_stats('CS2_PARTY_OWNER','CS2_BKG_RQST',method_opt=>' for columns size 254 SP_COMPANY_ID', cascade=>true);

10. Column Histogram

11. Review execution plan Driving table has the best filter Join method: Nested Loop or Hash Join Join order: Fewest number of rows are being returned to the next step Each table is being accessed efficiently index scan full table scan

12. Nested Loop For small number of rows(< 1000 ), with a good driving condition between the two tables

13. Hash Function

14. Hash Join For large data set(> 1000 ): The optimizer uses the smaller of two tables or data sources to build a hash table on the join key in memory

15. Access Path Full Table Scans Index Scans Index Unique Scans Index Range Scans Full Scans Fast Full Index Scans Index Joins

16. SQL Profile SQL Profiles are the new feature from 10g which is managed by Oracle Enterprise Manager as part of the Automatic SQL Tuning process. Apart from OEM, SQL Profiles can be managed through the DBMS_SQLTUNE package.

17. normal usage of SQL Profile Run the SQL Tuning Advisor Accept the recommended SQL Profile

18. advance usage: coe_xfr_sql_profile.sql coe_xfr_sql_profile.sql is from SQLT tool An easy way to lock the sql plan as outline

19.

20. Output sql format coe_xfr_sql_profile_<SID>_<PLAN_Hash_value>.SQL coe_xfr_sql_profile_chpub18xajb2w_1020905707.SQL

21. Q&A

Sql tuning guideline

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