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description= Optimize your Android app's performance by following best practices for SQLite databases, including configuration, schema design, query optimization, and troubleshooting.;
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designed to help you work smarter and faster case studies real world results from real world users explore how different teams use our tools to achieve their goals events programs get the details on upcoming webinars workshops meetups and special initiatives designed to help you grow documentation access detailed manuals api references and technical specifications to help you build and integrate with confidence english deutsch español américa latina français indonesia italiano polski português brasil tiếng việt türkçe русский עברית العربيّة فارسی हिंदी বাংলা ภาษาไทย 中文 简体 中文 繁體 日本語 한국어 android studio sign in app quality overview core value user experience technical quality privacy security essentials more design plan more overview core value user experience technical quality privacy security develop more google play more blog more android studio overview performance app performance guide get your app performance score memory overview about memory management memory allocation among processes manage your app s memory processes and threads set app memory budgets understanding and troubleshooting android memory introduction fundamental concepts quick assessment tools analyzing java memory bitmaps and memory analyzing native memory webview and memory app code is memory threads and memory memory locality and performance service bindings and process states system wide troubleshooting memory reclaim eviction and swap kswapd and lmkd interaction inspecting performance about inspecting performance profile types and when each is helpful android performance analyzer apa android studio profilers profiling and tracing choose the right profiling method capture real user data using profilingmanager overview how to capture a profile app driven profiling trigger based profiling retrieve and analyze profiling data query profilingmanager profiles set up a worker for profile uploading bulk trace analysis practical performance debugging example anr profiling limitations debug commands for local profiling system tracing overview capture trace capture a trace in android studio capture a trace on a device capture a trace from the command line navigate a report custom events define custom events custom trace events in native code in process tracing inspect gpu rendering benchmarking benchmark your app macrobenchmark writing a benchmark capture the metrics control your app adding instrumentation arguments microbenchmark about microbenchmark write a benchmark profile a benchmark microbenchmark instrumentation arguments microbenchmark and hilt building without gradle benchmarking in ci measure performance overview examples improving performance how to improve performance enable the r8 app optimizer enable app optimization optimize specified packages use r8 in full mode analyze r8 configuration choose libraries wisely adopt optimizations incrementally use keep rules about keep rules add global options add keep rules add additional rule types follow best practices keep rule use cases and examples advanced configurations target a build variant customize which resources to keep test the optimization troubleshoot r8 optimizations fix optimization problems use rules to troubleshoot optimization for library authors baseline profiles overview create baseline profiles create baseline profiles for a library configure baseline profile generation measure with macrobenchmark library manually create and measure baseline profiles debug baseline profiles case study android calendar startup profiles overview create startup profiles confirm optimization difference between baseline profiles and startup profiles app startup analyze and optimize app startup case study gmail wear os app startup library guides set up your environment for testing about background work declare a device performance class about app standby buckets about app hibernation verify app behavior on the android runtime art solving common problems app startup anrs keep your app responsive diagnose and fix anrs find the unresponsive thread rendering performance of rendering reducing overdraw performance and view hierarchies analyzing with profile gpu rendering improve layout performance battery and power optimize for doze and app standby monitor the battery level and charging state monitor connectivity status and connection metering determining and monitor docking state and type profile battery usage with batterystats and battery historian analyze power use with battery historian understand power management resource limits test power related issues background optimizations reduce app size hardware acceleration best practices for sqlite performance performance best practices monitoring performance about monitoring performance address common performance issues overview anrs crashes slow rendering slow sessions low memory killers lmks memory usage anonymous rss swap bitmap memory usage excessive wake locks stuck partial wake locks excessive wakeups excessive background wi fi scans excessive background network usage excessive battery usage permission denials app startup time dex code optimization jankstats library on google play android vitals healthy releases build ai experiences get started get started hello world developer verification adaptive apps compose for ui ai powered ide training monetization with play ️ optimize by form factor phones tablets foldables android for cars android tv android xr googlebook chromeos wear os build by category games camera media social messaging health fitness productivity enterprise apps get the latest latest updates experimental updates android studio preview jetpack compose libraries wear os releases privacy sandbox ️ excellent experiences learn more ui design design for android mobile desktop experiences xr headsets xr glasses ai glasses widgets wear os android tv android for cars architecture introduction libraries navigation modularization testing kotlin multiplatform quality overview core value user experience accessibility technical quality excellent experiences security overview privacy permissions identity fraud prevention gemini in android studio learn more get android studio core areas samples multidevice support user interfaces background work data and files connectivity all core areas ️ tools and workflow write and debug code build projects test your app performance command line tools gradle plugin api android bench device tech phones tablets foldables googlebook chromeos android for cars android tv android xr wear os android health better together all devices ️ libraries android platform jetpack libraries compose libraries google play services ️ google play sdk index ️ play console go to play console learn more ️ fundamentals play monetization play integrity android vitals play policies play programs ️ games dev center overview play asset delivery play games services play games on pc level up guidelines all play guides ️ libraries play feature delivery play in app updates play in app reviews play install referrer google play services ️ google play sdk index ️ all play libraries ️ tools resources android app bundles brand marketing play console apis ️ the android developer s blog read the latest explore the authors explore categories product news community how tos case studies events programs documentation android developers design plan app quality technical quality best practices for sqlite performance stay organized with collections save and categorize content based on your preferences android offers built in support for sqlite an efficient sql database follow these best practices to optimize your app s performance ensuring it remains fast and predictably fast as your data grows by using these best practices you also reduce the possibility of encountering performance issues that are difficult to reproduce and troubleshoot to achieve faster performance follow these performance principles read fewer rows and columns optimize your queries to retrieve only the necessary data minimize the amount of data read from the database because excess data retrieval can impact performance push work to sqlite engine perform computations filtering and sorting operations within the sql queries using sqlite s query engine can significantly improve performance modify the database schema design your database schema to help sqlite construct efficient query plans and data representations properly index tables and optimize table structures to enhance performance additionally you can use the available troubleshooting tools to measure the performance of your sqlite database to help identify areas that require optimization we recommend using the jetpack room library configure the database for performance follow the steps in this section to configure your database for optimal performance in sqlite enable write ahead logging sqlite implements mutations by appending them to a log which it occasionally compacts into the database this is called write ahead logging wal enable wal unless you are using attach database relax the synchronization mode when using wal by default every commit issues an fsync to help ensure that the data reaches the disk this improves data durability but slows down your commits sqlite has an option to control synchronous mode if you enable wal set synchronous mode to normal when opening the database val paramsbuilder sqlitedatabase openparams builder sqlitedatabase openparams builder paramsbuilder journalmode sqlitedatabase sync_mode_normal or after having opened the database db execsql pragma synchronous normal in this setting a commit can return before the data is stored in a disk if a device shutdown occurs such as on loss of power or a kernel panic the committed data might be lost however because of logging your database isn t corrupted if only your app crashes your data still reaches the disk for most apps this setting yields performance improvements at no material cost note if your app has multiple databases use the same synchronous setting everywhere in case there are data dependencies between different databases define efficient table schemas to optimize performance and minimize data consumption define an efficient table schema sqlite constructs efficient query plans and data leading to faster data retrieval this section provides best practices for creating table schemas consider integer primary key for this example define and populate a table as follows create table customers id integer name text city text insert into customers values 456 john lennon liverpool england insert into customers values 123 michael jackson gary in insert into customers values 789 dolly parton sevier county tn the table output is as follows rowid id name city 1 456 john lennon liverpool england 2 123 michael jackson gary in 3 789 dolly parton sevier county tn the column rowid is an index that preserves insertion order queries that filter by rowid are implemented as a fast b tree search but queries that filter by id are a slow table scan if you plan on doing lookups by id you can avoid storing the rowid column for less data in storage and an overall faster database create table customers id integer primary key name text city text your table now looks as follows id name city 123 michael jackson gary in 456 john lennon liverpool england 789 dolly parton sevier county tn since you don t need to store the rowid column id queries are fast note that the table is now sorted based on id instead of insertion order accelerate queries with indexes sqlite uses indexes to accelerate queries when filtering where sorting order by or aggregating group by a column if the table has an index for the column the query is accelerated in the previous example filtering by city requires scanning the entire table select id name where city london england for an app with a lot of city queries you can accelerate those queries with an index create index city_index on customers city an index is implemented as an additional table sorted by the index column and mapped to rowid city rowid gary in 2 liverpool england 1 sevier county tn 3 note that the storage cost of the city column is now double because it s now present in both the original table and the index since you are using the index the cost of added storage is worth the benefit of faster queries however don t maintain an index that you re not using to avoid paying the storage cost for no query performance gain create multi column indexes if your queries combine multiple columns you can create multi column indexes to fully accelerate the query you can also use an index on an outside column and let the inside search be done as a linear scan for example given the following query select id name where city london england order by city name you can accelerate the query with a multi column index in the same order as specified in the query create index city_name_index on customers city name however if you only have an index on city the outside ordering is still accelerated while the inside ordering requires a linear scan this also works with prefix inquiries for example an index on customers city name also accelerates filtering ordering and grouping by city since the index table for a multi column index is ordered by the given indexes in the given order consider without rowid by default sqlite creates a rowid column for your table where rowid is an implicit integer primary key autoincrement if you already have a column that is integer primary key then this column becomes an alias of rowid for tables that have a primary key other than integer or a composite of columns consider without rowid warning tables using without rowid can incur performance penalties if their primary keys are large for more information see the use cases store small data as a blob and large data as a file if you want to associate large data with a row such as a thumbnail of an image or a photo for a contact you can store the data either in a blob column or in a file and then store the path in the column files are generally rounded up to 4 kb increments for very small files where the rounding error is significant it s more efficient to store them in the database as a blob sqlite minimizes file system calls and is faster than the underlying filesystem in some cases note on android consider using a file for any data that is several multiples of 4 kb improve query performance follow these best practices to improve query performance in sqlite by minimizing response times and maximizing processing efficiency note many of the examples on this page include a limit clause this is good practice because queries that could return many rows have performance implications when returning large data sets the exception to this is for queries that implicitly return a size constrained dataset for example searching on a field defined as unique can only return zero or one row read only the rows you need filters let you narrow down your results by specifying certain criteria such as date range location ...
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