Sottoquery ed espressioni di tabella comuni (CTE)

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Questo esercizio fa parte del corso

Migliorare le prestazioni delle query in PostgreSQL

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Bundle up as you dive into the Winter Olympics! You will learn how to join, subquery, and create temporary tables while finding which Olympic athletes brave sub-freezing temperatures to train. You will also learn about the query planner and how its functionality can guide your SQL structure to faster queries.

Exercise 1: Tutto sui join Exercise 2: Da dove provengono tutti gli atleti Exercise 3: Usare join diversi per esplorare le regioni degli atleti Exercise 4: E il meteo?Exercise 5: Sottoquery ed espressioni di tabella comuni (CTE)

Esercizio in corso

Exercise 6: Filtrare fino al gelo con una sottoquery Exercise 7: Dove l'inverno è bianco Exercise 8: Paesi con subquery o CTE Exercise 9: Lavorare con le tabelle temporanee Exercise 10: Tabella temp dei canadesi Exercise 11: Analizza quella tabella temporanea

Dig up those past algebra memories while learning the SQL order of operations. Find which countries "should" have the most athletes by looking at population and gross domestic product (GDP) while learning the best way to filter. You will also learn when your query aggregates (sums, counts, etc.) and how you can structure your query to optimize this process.

Exercise 1: What you write is not what SQL sees Exercise 2: Order of operations impact on query structure Exercise 3: Group by and aggregations Exercise 4: Count and count distinct Exercise 5: Filtering in the WHERE clause Exercise 6: OR versus IN with athletes Exercise 7: Data type filters Exercise 8: EXPLAIN the filter query plan step Exercise 9: Filtering while joining Exercise 10: Where to place a region filter Exercise 11: Filtering in the join, where, and select Exercise 12: Aggregating with different data granularities Exercise 13: Aggregate before joining tables Exercise 14: South African trends

Zero in on the properties that improve database performance. Discover when your table is not a table but a view. Learn how your database's storage structure (row or column oriented) impacts your query structure. You will explore volcanic smog while using partitions and indexes to speed your queries.

Exercise 1: Queries and tables and views, oh my Exercise 2: Data loading and storage Exercise 3: Finding the table type Exercise 4: Row-oriented storage and partitions Exercise 5: Row-oriented storage properties Exercise 6: Previewing a row-oriented table Exercise 7: Partitioning on location Exercise 8: Using and creating indexes Exercise 9: Finding the database indexes Exercise 10: Creating and using an index Exercise 11: Compare runtimes Exercise 12: Using column-oriented storage Exercise 13: Column-oriented storage properties Exercise 14: Using the information schema

Learn the lingo of the Query Lifecycle and dive into the query planner. Explore how the query planner creates and optimizes the query plan. Find your next vacation locale by looking for countries with recent population growth while also seeing how a join impacts the query steps. Fine tune your optimization techniques by seeing how different filters speed your query times.

Exercise 1: Query lifecycle and the planner Exercise 2: Exploring pg_tables Exercise 3: Basic EXPLAIN Exercise 4: Index scans Exercise 5: EXPLAIN the WHERE Exercise 6: A deeper dive into EXPLAIN Exercise 7: EXPLAIN parameters Exercise 8: Aggregating and sorting populations Exercise 9: Joining in the query plan Exercise 10: Query structure and query execution Exercise 11: Subqueries vs. CTEs Exercise 12: Why the difference?Exercise 13: Filtering impacts Exercise 14: Congratulations