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Database Indexing Strategies
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In this article, we are going to explore effective database indexing strategies. Database performance is critical to any large-scale, data-driven application. Poorly designed indexes and a lack of indexes are primary sources of database application bottlenecks. Designing efficient indexes is critical to achieving good database and application performance. As databases grow in size, finding efficient ways to retrieve and manipulate data becomes increasingly important. A well-designed indexing strategy is key to achieving this efficiency. This article provides an in-depth look at index architecture and discusses best practices to help us design effective indexes to meet the needs of our application.
Basics of Indexing
Let's start with the basics of indexing in databases. An index, much like the index at the end of a book, is a data structure that speeds up data retrieval operations. Just as a book index lists keywords alongside page numbers to help locate information quickly, a database index serves a similar purpose, speeding up data retrieval without needing to scan every row in a database table.
The structure of a database index includes an ordered list of values, with each value connected to pointers leading to data pages where these values reside. Index pages hold this organized structure which provides a more efficient way to locate specific information.
Indexes are typically stored on disk. They are associated with a table to speed up data retrieval. Keys made from one or more columns in the table make up the index, which, for most relational databases, are stored in a B+ tree structure. This structure allows the database to locate associated rows efficiently.
Finding the right indexes for a database is a balancing act between quick query responses and update costs. Narrow indexes, or those with fewer columns, save on disk space and maintenance, while wide indexes cater to a broader range of queries. Often, it requires several iterations of designs to find the most efficient index.
In its simplest form, an index is a sorted table that allows for searches to be conducted in O(Log N) time complexity using binary search on a sorted data structure.
Various data structures, such as B-Trees, Bitmaps, or Hash Maps, can be used to implement indexes. Though all these structures offer efficient data access, their implementation details differ.
For relational databases, indexes are often implemented using a B+ Tree, which is a variant of B-Tree.
Primer on B+ Tree
The B+ Tree is a specific type of tree data structure, and understanding it requires some background on its predecessor, the B-Tree.
The B-Tree, or Balanced Tree, is a self-balancing tree data structure that maintains sorted data and allows for efficient insertion, deletion, and search operations. All these operations can be performed in O(Log N) time.
Here’s what distinguishes the structure of a B-Tree:
All leaves are at the same level - this is what makes the tree 'balanced'.
All internal nodes (except for the root) have a number of children ranging from d (the minimum degree of the tree) to 2d. The root, however, has at least two children.
A non-leaf node with ‘k' children contains k-1 keys. This means if a node has three children (k=3), it will hold two keys (k-1) that segment the data into three parts corresponding to each child node.
The B-Tree is an excellent data structure for storing data that doesn't fit into the main memory because its design minimizes the number of disk accesses. And because the tree is balanced, with all leaf nodes at the same depth, lookup times remain consistent and predictable.
The B+ Tree is a variant of the B-Tree and is widely used in disk-based storage systems, especially for database indexes. The B+ Tree has certain unique characteristics that improve on the B-Tree.
In a B+ Tree, the data pointers (the pointers to the actual records) are stored only at the leaf nodes. The internal nodes only contain keys and pointers to other nodes. This means that many more keys can be stored in internal nodes, reducing the overall height of the tree. This decreases the number of disk accesses required for many operations.
All leaf nodes are linked together in a linked list. This makes range queries efficient. We can access the first node of the range and then simply follow the linked list to retrieve the rest.
In a B+ Tree, every key appears twice, once in the internal nodes and once in the leaf nodes. The key in the internal nodes acts as a division point for deciding which subtree the desired value could be in.
These features make B+ Trees particularly well-suited for systems with large amounts of data that won't fit into main memory. Since data can only be accessed from the leaf nodes, every lookup requires a path traversal from the root to a leaf. All data access operations take a consistent amount of time. This predictability makes B+ Trees an attractive choice for database indexing.
A comparison between B-Tree vs B+ Tree Now we understand how B+ Tree is used for indexing, let’s see how a typical database engine uses it to maintain indexes.
Clustered Index
A clustered index reorders the way records in the table are physically stored. It does not store rows randomly or even in the order they were inserted. Instead, it organizes them to align with the order of the index, hence the term “clustered”. The specific column or columns used to arrange this order is referred to as the clustered key.
The arrangement determines the physical order of data on disk. Think of it as a phonebook, which is sorted by last name, then first name. The data which is phone number and address is stored along with the sorted index.
(maybe a picture of how a phone book works?)
However, because the physical data rows can be sorted in only one order, a table can have only one clustered index. Adding or altering the clustered index can be time-consuming, as it requires physically reordering the rows of data.
It's also important to select the clustered key carefully. Typically, it's beneficial to choose a unique, sequential key to avoid duplicate entries and minimize page splits when inserting new data. This is why, in many databases, the primary key constraint automatically creates a clustered index on that column if no other clustered index is explicitly defined.
However, an exception to this general guidance is PostgreSQL. In PostgreSQL, data is stored in the order it was inserted, not based on the clustered index or any other index. However, PostgreSQL provides the CLUSTER command, which can be used to reorder the physical data in the table to match a specific index. It's important to note that this physical ordering is not automatically maintained when data is inserted or updated - to maintain the order, the CLUSTER command needs to be rerun.
Non-clustered Index
Non-clustered indexes are a bit like the index found at the back of a book. They maintain a distinct list of key values, with each key having a pointer indicating the location of the row that contains that value. The pointers tie the index entries back to the data pages.
Since non-clustered indexes are stored separately from the data rows, the physical order of the data isn't the same as the logical order established by the index. This separation means that accessing data using a non-clustered index involves at least two disk reads, one to access the index and another to access the data. This is in contrast to a clustered index, where the index and data are one and the same.
A major advantage of non-clustered indexes is that we can have multiple non-clustered indexes on a table, each being useful for different types of queries. They are especially beneficial for queries involving columns not included in the clustered index. They enhance the performance of queries that don't involve the clustered key or don't require scanning a range of data.
It's important to consider the trade-off. While non-clustered indexes can speed up read operations, they can slow down write operations, as each index must be updated whenever data is modified in the table. It's crucial to strike a balance when deciding the number and type of non-clustered indexes for a given table.
Understanding Index Types
Indexes speed up data retrieval by providing a more efficient path to the data without scanning every row. There are different types of indexes. We’ll take a look at the common ones.
Primary Index
The primary index of a database is typically the main means of accessing data. When creating a table, the primary key often doubles as a clustered index, which means that the data in the table is physically sorted on disk based on this key. This ensures quick data retrieval when searching by the primary key.
The efficiency of this setup largely depends on the nature of the primary key. If the key is sequential, writing to the table is generally efficient. But if the key isn't sequential, reshuffling of data might be needed to maintain the order. This can make the write process less efficient.
Note that while the primary key often serves as the clustered index, this is not a hard and fast rule. The clustered index could be based on any column or set of columns, not necessarily the primary key.
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Private markets’ bumpy ride—and what it means for 2023
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ON PRIVATE MARKETS
Lessons from private markets’ up-and-down year
John SpiveyEarlier this spring, McKinsey’s Global Private Markets Review—our flagship report examining private-markets data from the previous year—told a tale of two halves. There was a robust first half of the year, and a second half during which it often felt like the sky was falling. As the Federal Reserve started increasing interest rates to fight inflation, debt became both more expensive and more difficult to obtain. This development, combined with the decline in public markets, put downward pressure on deal volume, fundraising, and valuations in the private markets.
Many of these trends persisted through the first half of 2023 and may continue to shape the market going forward. That’s why a retrospective report like ours can be instructive for managers and investors making strategic decisions. The report is intended to help private-market players evaluate the trends that shape private markets and make more informed strategic, operational, and portfolio-related decisions.
Our review revealed several notable highlights, along with some surprises. Private-markets fundraising declined 11 percent from 2021, falling to $1.2 trillion. Many institutional investors were affected by the denominator effect, whereby falling public-market allocations increased the relative weight of their private-market holdings. Dealmaking also declined as financing alternatives became less attractive and valuations less certain, with 2022 private equity volumes down 26 percent from the prior year.
Surprisingly, however, 2022 was still the second-best year ever for both fundraising and deal volume, according to our analysis. Why was activity so strong, especially in what felt like such a challenging year? The simplest explanation is that “tale of two halves.” While the market slowed dramatically in the second half of 2022—which was one of the slowest dealmaking environments of the past several years—the frenetic pace in the first half of the year had already ensured robust full-year tallies.“2022 was a ‘tale of two halves’: there was a robust first half of the year, and a second half during which it often felt like the sky was falling.”
Highlights among asset classes and strategies include private debt and infrastructure fundraising, which gained 2.1 percent and 6.5 percent, respectively, even as private markets’ two largest asset classes—private equity and real estate—saw year-over-year double-digit fundraising declines. The relative success of these two strategies amid market turmoil is partly the result of their stability: of the private-asset classes, debt and infrastructure tend to have the lowest performance volatility and greatest degree of inherent downside protection. The pace of inquiries we have had from companies interested in launching or expanding into these asset classes has picked up noticeably in the past six to 12 months.
Sustainable investing thrived in 2022, buoyed by the energy transition and new government policies, including the US Inflation Reduction Act. Fundraising that focused on environmental, social, and governance initiatives totaled $24 billion in the first half of the year, already almost as much as the previous full-year record of $28 billion. And sustainability-related investments increased by 7 percent to nearly $200 billion, a new record, proving resilient to the dealmaking headwinds affecting private markets overall.
In the first half of 2023, we saw a different market sentiment emerge as private-market players adapted to the realities of the new environment that took hold in the past year. Managers are establishing new financing relationships and updating value creation assumptions to account for the reality that debt is more than 50 percent more expensive than it was a year ago. Sellers and buyers are gradually adjusting expectations on asset prices (though this process is far from complete). And general partners are adjusting fundraising expectations and approaches to account for the fact that limited partners plan to commit less capital to private markets this year.ABOUT THE AUTHOR
John Spivey is an associate partner in McKinsey’s Charlotte office.
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Where is the world economy heading? See the key trends.
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• US inflation cools. The pace of inflation in the US slowed to 4.0% in May 2023, its lowest point in two years (after spiking to 9.1% in June 2022), government data reveals. Decreasing energy prices and a small uptick in food costs contributed to the decline. Some economists are keeping a close eye on housing inflation; costs related to housing went up 0.6% in May. Current conditions are “encouraging,” but the US might still experience an economic slowdown, albeit a delayed one, a chief economist said. [FT]
• Inflation still top of mind. Central banks across the world are looking to maintain interest rate interventions in the hopes of tempering inflation rates. In many regions and countries, inflation continues to moderate but generally remains high. Interest rates and sentiment are weighing on growth projections, and the picture is somewhat patchy, explain Sven Smit, McKinsey’s chair of insights and ecosystems and chair of the McKinsey Global Institute, and colleagues. Growth in some emerging economies such as China and India are outpacing developed economies.
• Uneven growth. In advanced economies, inflation in the US has declined, partly due to falling energy prices. Energy prices also came down in the eurozone, although food prices remain high, and experts believe the UK may be able to avoid a recession in 2023. Meanwhile, India is set to contribute around 15% to global growth, making it one of the world’s fastest-growing economies. Dive deeper into McKinsey’s macroeconomic data and analysis of the world economy to understand key global trends and risks.
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The sharper edge: A leader’s guide to competitive advantage
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Companies can distinguish themselves in many ways. Besides such classic differentiators as cost or products, today’s competitive advantages can come from a variety of sources, such as new business models, disruption, culture, and technology. But in a highly competitive environment, finding a “superpower” and nurturing it may require the entire organization to pitch in, with visionary leadership at every level. This week, we explore some effective practices to build and sustain what makes your organization unique.
Few business leaders can afford to ignore this game-changing technology. In the view of McKinsey experts, “CEOs should consider exploration of generative AI a must, not a maybe. Generative AI can create value in a wide range of use cases.... The downside of inaction could be quickly falling behind competitors.” Options range from deploying specific generative-AI features on a smaller scale to implementations that can transform entire businesses. For example, one company uses an off-the-shelf generative-AI coding tool to improve productivity, whereas another has built and trained a foundation model from scratch to accelerate scientific research—a high-cost, resource-intensive process. To organize for generative AI, it may be best to start by convening a cross-functional group of the company’s leaders to identify and prioritize where the technology could generate the most value.
That’s the number of capabilities that companies need to build to outperform the competition, according to McKinsey senior partners Eric Lamarre, Kate Smaje, and Rodney Zemmel. In their new book, Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI, the authors discuss what it takes for leaders to spark transformation across all six capabilities. A key step involves adopting a new operating model that brings business, technology, and operations closer together. “The shift to a new operating model is the signature move of CEOs in rewiring the company,” say the authors. “Only they can catalyze such large-scale organizational change.”
That’s McKinsey senior partner Carolyn Dewar and colleagues on how continuous-improvement practices can deliver a competitive edge for organizations. “Sometimes those improvements are big, often they are small,” say the McKinsey experts. “But what’s most important is they’re frequent.” For example, to increase performance transparency—an essential practice for continuous improvement—one company tracked capital asset utilization across different areas of its operations. Finding many assets that were poorly utilized, the teams that were using them channeled their energies into making the assets more productive—generating a 20 percent productivity leap in less than two months.
“I honestly believe that culture is a critical competitive weapon,” says Harvard Business School professor emeritus James Heskett in a discussion with McKinsey. But few leaders take the time to create a strong organizational culture. “We all agree that we need to address it, but it takes too long to do it,” Heskett says. “It’ll probably have to be handed off to some other leader.” Culture may be even more difficult to nurture in a hybrid environment where people in different geographic locations and work settings need to work together productively. In such cases, “An effective culture will ensure that there is adequate advocacy, that there is the right amount of face-to-face contact, and that certain really important values come to the fore: inclusion and voice,” says Heskett.
Corporate culture can be a major competitive advantage, but it can be hard to define. As the author of an Economist article puts it, “There is no substitute for being at a firm day in, day out, if you want to understand what it is really like.” One person’s idea of a good culture may be Ping-Pong tables and catered lunches, whereas another may prefer an inspiring mission statement. But most leaders would agree that a large part of building a robust culture lies in creating shared values and beliefs that govern how the organization works. This strategy has worked for smart-energy company Tibber, which credits much of its rapid growth to its sense of purpose. “At our core, I think all humans yearn for that,” says chief technology officer Richard Eklund in a McKinsey interview. “I feel we’ve arrived at an inflection point where purpose is becoming even more important than compensation.”
Lead with a competitive edge.
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by "McKinsey Leading Off" <publishing@email.mckinsey.com> - 02:19 - 3 Jul 2023 -
What potential paths could the global economy take from now to 2030?
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• A fragile recovery. The world economy is expected to make a tenuous recovery in 2023 and 2024 as inflation and elevated interest rates continue to affect banking, consumer spending, and growth, according to the OECD. Although the economy is improving, risks abound, including the ongoing war in Ukraine and rising debt in developing nations. Global GDP is now projected to grow 2.7% in 2023, a 0.5% increase from the OECD’s previous forecast. Economies in Asia—including China, India, and Singapore—will fuel much of that growth. [AP]
• It’s one thing on paper. Asset price inflation over the past two decades created about $160 trillion in wealth—on paper. At the same time, economic growth was sluggish, inequality rose, and every $1.00 in investment ended up generating $1.90 in debt. With recent turbulence in the banking sector and heightened geopolitical tensions, conditions have changed from the years of loose money and seemingly endless increases in wealth, according to Sven Smit, McKinsey’s chair of insights and ecosystems and of the McKinsey Global Institute, and colleagues.
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Top 10 reports this quarter
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Our top ten reports this quarter look at the state of organizations, how to accelerate productivity growth, and more. At No. 1, Michael Chui, Eric Hazan, Roger Roberts, Alex Singla, Kate Smaje, Alex Sukharevsky, Lareina Yee, and Rodney Zemmel reveal how gen AI could unlock trillions of dollars in value across sectors.
Africa’s economy downshifted over the last decade, yet half of its people live in countries that have thrived on the continent. Africa has the human capital and natural resources to accelerate productivity and reimagine its economic growth, which is, more than ever, vital for the welfare of the world. Download the full report
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by "McKinsey Top Ten" <publishing@email.mckinsey.com> - 03:39 - 2 Jul 2023 -
The week in charts
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by "McKinsey Week in Charts" <publishing@email.mckinsey.com> - 03:57 - 1 Jul 2023
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