Performance Tuning SQL Queries in Fabric Warehouse

You can make your queries much faster with performance tuning in Fabric Warehouse. This platform has special features that change how your queries work:

• Fabric Warehouse is built for the cloud and keeps your data safe, so your results are always the same.

• It saves data in Parquet files that cannot be changed, which lets you undo changes fast if you need to.

• It makes storage better and speeds up reading by cleaning up data and saving checkpoints, even when lots of people use it at once.

• The Massively Parallel Processing (MPP) system lets you handle big jobs, but some tasks might get slower if they do not grow well.

• Filtering early, picking the right data types, and making data go in better all help your queries run faster.

These features give you many ways to make your queries work better.

Key Takeaways

• Filter data early and pick only the columns you need. This makes your queries faster and saves resources.

• Use partitioning and indexing to organize your data. This helps scan less data and makes queries quicker.

• Look at query insights and execution plans often. This helps you find and fix slow or expensive queries.

• Add foreign keys and use materialized views. These help the system handle hard queries faster and easier.

• Test your queries with real data and watch how the system works. This keeps your warehouse running well and efficiently.

Performance Tuning Basics

Performance tuning in Fabric Warehouse helps your SQL queries run faster. It also helps them use less computer power. You do this by learning how the system keeps and uses your data. Fabric Warehouse is built in the cloud and spreads your data over many nodes. This means you can work with lots of data at the same time. You should know how this setup changes how you tune your queries.

Key Factors

You can make queries faster by looking at some key things. The table below lists the main things that change how fast queries run in Fabric Warehouse:

Table detailing factors for performance tuning SQL queries, including Partition Option, Degree of Copy Parallelism, Isolation Level, Intelligent Throughput Optimization (ITO), Source Table Physical Design, Data Movement Region, and Developer Effort with their descriptions and impacts on SQL query performance.

Fabric Warehouse helps by doing some jobs for you. It compacts data and updates statistics on its own. You do not need to run VACUUM or OPTIMIZE as much as in other systems. V-Order optimization and pre-warming the cache also make queries faster.

OLAP vs OLTP

It is important to know the difference between OLAP and OLTP systems. OLTP systems do simple and quick jobs, like adding a sale or changing a customer record. These systems are best for small and fast queries. If you run big reports on OLTP, they get slow and may not work well.

Fabric Warehouse is made for OLAP jobs. OLAP systems keep lots of old data and let you run hard queries, like finding patterns or making guesses about the future. You can use star or snowflake schemas to make these queries faster. Keeping OLAP and OLTP jobs apart helps both work better. Fabric Warehouse uses features like compute-storage separation and auto-scaling. These help it handle big jobs without slowing down your daily work.

Identifying Bottlenecks

When you want to make your SQL queries faster in Fabric Warehouse, you need to find out what slows them down. This step is important for Performance Tuning. You can use built-in tools and views to spot problems before you try to fix them.

Query Insights

You can start by looking at query insights. These insights help you see what is happening inside your warehouse. They show you which queries use the most resources and which ones run for a long time. Here are some common bottlenecks you might find:

• Long-running queries often slow down your system. You can find them by checking system views like long_running_queries.

• Some queries use too much CPU. This usually means the query design is not good or the operation needs a lot of resources.

• If your queries scan too much data from remote storage instead of using the cache, they will run slower.

• Complex or large queries can use up all your resources and even cause timeouts.

• Poorly designed queries increase CPU and memory use, which hurts performance for everyone.

💡 Tip: Power Query can freeze or fail when you try to filter or join large datasets. If you use T-SQL in Fabric Warehouse, you can finish these jobs much faster and avoid crashes.

You can use Dynamic Management Views (DMVs) to get more details. DMVs like sys.dm_exec_connections, sys.dm_exec_sessions, and sys.dm_exec_requests let you see which queries are running, how long they take, and how much CPU or memory they use. You can also use special views like queryinsights.long_running_queries to find trends and spot which queries run too often or take too long.

Here is a table that shows the types of query insights you can use:

Table displaying SQL query insights for performance tuning in Fabric Warehouse, including CPU Consumption, User Connections, Requests Per Second, Blocked Queries per Second, Allocated Size, and Automatic Index with corresponding descriptions.

You should check these insights often. They help you find slow spots before they become big problems.

Execution Plans

After you find slow queries, you need to see how the system runs them. You do this by looking at execution plans. An execution plan is like a map that shows every step the database takes to answer your query.

You can spot many problems by reading execution plans:

• Full table scans mean the system reads every row in a table. This often happens when you do not have the right indexes.

• Costly join operations, like nested loops between big and small tables, show you need better indexing.

• Cardinality estimation problems happen when the system guesses wrong about how many rows it will get. This can happen if your statistics are old.

• Sorting and grouping without good indexes use too many resources.

• High-cost operators in the plan show where the system uses a lot of CPU or disk. These are good places to start your tuning.

🛠️ Note: You can use commands like SET STATISTICS IO ON and SET STATISTICS TIME ON to see how many logical reads and how much CPU time your queries use. Focus on the parts with the highest numbers.

Here is a simple way to analyze execution plans:

1. Look at the plan to see each step the system takes.

2. Find full table scans and costly joins. These often slow down your queries.

3. Check for high-cost operators that use a lot of CPU or disk.

4. Use statistics commands to match high logical reads or CPU time with steps in the plan.

5. Fix problems by adding indexes, updating statistics, or changing your query.

You can also use real-time profiling tools to watch resource use as your query runs. This helps you confirm where the bottlenecks are. By combining execution plan analysis with query insights, you can target your Performance Tuning efforts and make your queries much faster.

Query Optimization

Query Structure

You can make your SQL queries faster by writing them the right way. Fabric Warehouse is not the same as regular SQL Server systems. For example, you cannot use identity columns or default constraints here. You must find other ways to make unique keys and set default values. ALTER TABLE commands have some limits, so plan your table changes before you start. If you know these rules, you can write better queries and avoid slowdowns.

Here are some tips to help you write faster queries:

• Use SELECT statements that only ask for the columns you need.

• Add filters early in your query. This is called predicate pushdown. It helps the system skip rows you do not want.

• Do not use SELECT * because it makes the system scan more data.

• Write joins carefully. Try to join on indexed columns.

• Use WHERE clauses to limit data before joining tables.

💡 Tip: Always check if you can filter data before loading it. This saves computer power and helps your queries finish faster.

Think about how your data is stored. Fabric Warehouse uses partitioned data and supports virtualization. You can use shortcuts to look at data in other workspaces without copying it. This makes your queries faster and keeps storage costs low.

V-Ordering

V-Ordering is a special feature in Fabric Warehouse that helps your queries read data faster. When you load data, the system sorts and organizes it to make reading quick. V-Ordering uses sorting, row group distribution, and special encoding before compressing the data. This process cuts down the amount of data the system needs to scan and helps compress the data better.

V-Ordering is turned on by default. It usually makes your read queries about 10% faster. You will see the biggest improvements when you use Power BI Direct Lake or run SQL Endpoint queries. The system uses less network bandwidth, disk space, and CPU power because it reads only what you need.

But V-Ordering can slow down write operations by 10-20% because it takes extra work to organize the data. If you mostly read data, keep V-Ordering on. If you write data a lot, you may want to test if turning it off helps. V-Ordered files work with any Parquet reader, but files without V-Order may not read as quickly.

⚠️ Note: V-Ordering does not help with Spark workloads. It can make Spark reads up to 50% slower. Always check your workload before changing this setting.

Indexing & Partitioning

You can make your queries faster by using indexing and partitioning. Fabric Warehouse does not use traditional RANGE or HASH partitioning. Instead, it stores data in partitioned Delta tables. You can organize your data in folders like /year=2024/month=06/day=01. When you filter on these columns, the system only scans the folders it needs. This is called partition pruning. It makes your queries much faster because the system skips data you do not need.

Partitioning works best for time-series data or tables that grow fast. You can use dynamic partitioning to keep your data balanced and avoid slowdowns from too much data in one place. Indexing helps too. Fabric Warehouse adds an auto-incrementing column called Index_Num. This makes it easier to run queries that need to find rows in order.

Here is a table to show how indexing and partitioning help:

Table illustrating SQL query performance tuning techniques in a fabric warehouse context, with methods such as partitioning, indexing, and partition pruning. The table explains how these techniques reduce data volume, speed up searches, and save time by skipping unnecessary folders.

🛠️ Tip: Always filter on partition columns like year or month. This lets the system use partition pruning and finish your queries faster.

When you use both indexing and partitioning, you get the best results. Your queries run faster, use less computer power, and cost less. These strategies are important for Performance Tuning in Fabric Warehouse.

Schema Design Impact

Foreign Keys

You can make queries faster in Fabric Warehouse by using foreign keys in your schema. Fabric Warehouse does not check foreign keys at the engine level. But you still get many good things by adding them.

• Foreign keys help tools like Power BI find table relationships on their own.

• You get the right joins in reports, so you do not write join rules each time.

• Query folding and auto-joins work better, so your queries run faster and more often.

• The query optimizer uses foreign key information to pick better join plans and skip slow joins.

• Your data model is easier to understand, and analysts can build reports with correct totals without extra work.

• Even if the system does not check foreign key rules, you still get better links with the semantic layer and more standard queries.

💡 Tip: Always add foreign keys to your tables. This helps the query engine and your reporting tools work better and faster.

Materialized Views

Materialized views are a strong way to make hard queries run faster. When you make a materialized view, Fabric Warehouse saves data that is already joined and grouped. This means you do not need to redo big joins or groupings every time you run a query.

• The system can use materialized views by itself, so you do not need to change your queries.

• Materialized views update with your main tables, so your results stay up to date.

• You can use different ways to spread out data to match your queries and get even better speed.

• Materialized views can cut down joins and remove costly shuffle steps, making your queries much faster.

• The system keeps materialized views in a clustered columnstore index and handles changes in the background, so you do not need to worry about upkeep.

If you run reports or dashboards that use the same math often, materialized views help you get answers fast. You save time and computer power, and your users see results sooner.

Testing & Measurement

Performance Testing Steps

You need a simple plan to test your SQL queries in Fabric Warehouse. Follow these steps to see how well your queries work:

1. Move data from your Lakehouse to the Warehouse. Use copy flows with staging turned on. This step checks if your data moves the right way.

2. Run big SQL queries. Try counts, picking unique values, and joining big tables. Use datasets with billions of rows to see how the system handles lots of work.

3. Watch how long your queries take. Use tools like the Fabric Capacity App and Onelake File Explorer. These tools show when files are made and how long each query takes.

4. Check how much capacity you use. Look at certain times to find jobs that run long or use lots of resources. See if you go over your set capacity or burst above it.

5. Compare results on different capacity SKUs, like F2 and F64. This helps you see how making your system bigger or smaller changes speed.

6. Use what you learn to change your workloads and plan your capacity. This step helps you get the best results from Performance Tuning.

💡 Tip: Always test with real data sizes and real jobs. This gives you the most correct results.

Analyzing Results

After testing, you need to look at your results to find ways to make things better. Focus on these main metrics:

• CPU usage

• Memory use

• Query run time

• Dataset refresh speed

• Capacity throttling events

• Background jobs and task queues

You can use different tools to help you look at your results:

Table illustrating SQL performance tuning tools in Fabric Warehouse with columns for Tool/Feature, What It Does, and Key Metrics You See. Includes Query activity, Query insights, and Dynamic Management Views (DMVs) with their respective descriptions and metrics.

If you see high CPU or memory use, or lots of throttling, you need to make things better. Try to use fewer columns and do less math in your queries. Pick the smallest data types you can. Design your tables with a star schema to read fewer rows. Keep your statistics up to date for better plans. If things are still slow, think about getting more capacity or setting up surge protection.

🛠️ Note: Checking your system often helps you find problems early. Use dashboards in the Fabric Capacity Metrics App to watch your system’s health and see trends over time.

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You can make queries faster in Fabric Warehouse by planning your schema well, splitting data into parts, and using materialized views. Run queries often to keep your data ready and check your system so it does not get slow. For the best speed, use only one SQL Analytics Endpoint and one Warehouse in each workspace. Look out for new tools like automatic index making, quick data copying, and smart AI helpers. Test your queries a lot and change your plan as Fabric gets new updates.

• Use just one SQL Analytics Endpoint and one Warehouse in each workspace

• Save query answers with materialized views when you can

• Make delta tables better with OPTIMIZE

• Run queries often so data stays in memory

• Check how much system power you use

• Try new things like auto tuning and AI helpers

FAQ

How do you know if your query needs tuning?

You should check query run times and resource use. If you see slow results or high CPU, your query needs tuning. Use built-in tools like Query Insights to spot slow queries. Fast queries help you save time and system power.

What is the best way to speed up a slow query?

Start by filtering data early in your query. Use partition columns in your WHERE clause. Avoid SELECT *. Check your execution plan for full table scans. Add indexes if needed. These steps help you get faster results.

Can you use indexes in Fabric Warehouse like in SQL Server?

Fabric Warehouse uses auto-incrementing columns and partitioned Delta tables instead of classic indexes. You should filter on partition columns to help the system skip data. This method works best for large tables and time-based data.

Why does V-Ordering sometimes slow down writes?

V-Ordering sorts and organizes data for faster reads. This extra step takes more time when you write data. If you write data often, test your workload with and without V-Ordering to see which works better for you.

How can you monitor query performance over time?

You can use the Fabric Capacity Metrics App and Query Insights. These tools show trends in query speed, CPU use, and memory. Set up dashboards to watch for slowdowns. Regular checks help you keep your system running well.