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❤️ Tokio"},"https://fdb-rs.github.io/authors/":{"body":"The authors of the blog articles.\n","id":"https://fdb-rs.github.io/authors/","title":"Authors"},"https://fdb-rs.github.io/authors/rajivr/":{"body":"Contributor to fdb-rs.\n@rajivr\n","id":"https://fdb-rs.github.io/authors/rajivr/","title":"Rajiv M Ranganath"},"https://fdb-rs.github.io/blog/":{"body":"","id":"https://fdb-rs.github.io/blog/","title":"Blog"},"https://fdb-rs.github.io/blog/fdb-crate-3-0-1/":{"body":"I am happy to announce fdb crate version\nv0.3.1 has been\nreleased. This is the first release in the v0.3.x series and provides\nsupport for FoundationDB client API version 710 using cargo feature\nflag fdb-7_1.\nFollowing are the API changes and new features in this release.\n\n\nThe\nRange\ntype now has a\ninto_parts\nmethod that lets you easily de-structure a Range value. When you\nhave an owned Range value, and you would like owned values of its\nparts, then you can use this method and avoid unnecessary\nclone(). The\ninto_parts idiom is also available on\nKeyValue\nand\nMappedKeyValue\ntypes.\n\n\nThe\nReadTransaction\ntrait has support for\nget_range_split_points\nwhich is an API version 710 feature.\n\n\nThe\nReadTransaction\ntrait also has support for the\nget_mapped_range\nfeature, which is an experimental feature in FoundationDB 7.1. This\nfeature is automatically enabled when you use the cargo feature\nflag fdb-7_1.\nThe Range type now includes a\ninto_mapped_stream\nmethod that returns a stream (asynchronous iterator) of\nMappedKeyValue.\nYou can find more information about the GetMappedRange feature\nhere. get_mapped_range.rs\nprovides an example of how this feature can be used.\n\n\nFoundationDB\nTenant support\nis another experimental feature whose support is included in this\nrelease. Tenant support is also automatically enabled when you use\nthe cargo feature flag fdb-7_1.\nIn the bindings Tenant support is implemented using types\nTenant,\nFdbTenant\nand\nTenantManagement. The\nopen_tenant\nmethod on FdbDatabase provides a way to create a value of\nFdbTenant type and work with tenants in the cluster.\n\n\nWith the release of v0.3.x series, support for cargo feature flag\nfdb-6_3 is deprecated. We will continue to support the cargo feature\nflag fdb-6_3 in subsequent v0.3.x releases. It would be removed in\nv0.4.x release, when support for API version 720 and cargo feature\nflag fdb-7_2 would be introduced. Please plan your migrations\naccordingly.\nI would like to say a big thank you to the FoundationDB community for\ntheir support and answering my questions in the forums. This release\nwould not have been possible without your help!\nPlease contact us if you have any\nquestions or feedback.\n","id":"https://fdb-rs.github.io/blog/fdb-crate-3-0-1/","title":"fdb crate v0.3.1 released"},"https://fdb-rs.github.io/blog/introducing-fdb-crate/":{"body":"I am happy to announce the release of the\nfdb crate, which provides\nFoundationDB client API for\nTokio. You can find guide-level documentation for\nthe fdb crate here.\nFoundationDB is a distributed key-value store with strict\nserializable ACID\ntransactions. FoundationDB is known for its reliability and\nscalability.\nTokio and FoundationDB are complementary technologies for building\ncloud-scale applications. Tokio runtime and its ecosystem of crates\nsuch as Tower, Hyper, Tonic, gives us a great way to develop\napplications whose state can be managed using FoundationDB.\nIn the fdb-rs GitHub organization,\ntogether with the Tokio and FoundationDB community, I hope to develop\ncrates related to FoundationDB that work well with the Tokio ecosystem\ncrates.\nOur first crate is the fdb crate. It is also a foundational crate that\ninteracts with the C library. The fdb crate provides idiomatic Tokio\nand Rust APIs that we can use directly in our applications and also to\nbuild other crates. In FoundationDB terminology the latter crates\nwould be referred to as\nlayers.\nNo conversation around FoundationDB would be complete without a word\nabout correctness and testing.\nUnder the hood, most of the fdb crate is written in a functional\nprogramming style. FoundationDB has a tuple\nlayer\nwhich provides a standardized mechanism of converting key-value byte\nstrings into a\ns-expression like data\nconstruct. Parsing code for the tuple layer is written using the\nexcellent nom parser-combinator\nlibrary.\nWithin the fdb crate when doing asynchronous range reads of key-value\npairs and converting them into a Tokio stream, there is a need to run\na state machine. For correctness and understandability, this state\nmachine\nhas been modeled using\nsismic.\nBesides regular unit and integration tests, the fdb crate continuously\nruns\nthousands\nof simulation tests which checks the bindings using a mechanism called\nbinding\ntester. Official\nFoundationDB bindings for other languages are tested this way, and we\ndo the same for our Tokio Rust bindings.\nAt this point the fdb crate is reasonably stable, and I do not expect\nany major API changes to it. Most of the future work will be focused\non adding upcoming FoundationDB 7.x support to the fdb crate and\nexploring how we can create a minimal\nrecord-layer like\ncrate for Tokio.\nTokio and FoundationDB community members have been extremely helpful\nin making the fdb crate happen.\nFrom the Tokio community, I would like to thank Alice\nRyhl who answered many Tokio related questions on\nDiscord.\nFrom the FoundationDB community, I would like to thank Alec\nGrieser, Andrew\nNoyes,\nA.J. Beamon, Jingyu\nZhou, Alex\nMiller and Pierre\nZemb for providing\ndetailed replies to my questions on the FoundationDB forum.\nThe fdb crate would not have been possible without your help!\n","id":"https://fdb-rs.github.io/blog/introducing-fdb-crate/","title":"Introducing FoundationDB Client API for Tokio"},"https://fdb-rs.github.io/docs/":{"body":"","id":"https://fdb-rs.github.io/docs/","title":"Docs"},"https://fdb-rs.github.io/docs/crate-fdb/":{"body":"","id":"https://fdb-rs.github.io/docs/crate-fdb/","title":"fdb crate"},"https://fdb-rs.github.io/docs/crate-fdb/class-scheduling-tutorial/":{"body":"Full working code for concepts described in this section is\nhere.\nThis tutorial provides a walk through of designing and building a\nsimple application in Tokio and Rust using FoundationDB. In this\ntutorial, we use a few simple data modeling techniques. For a more\nin-depth discussion on data modeling in FoundationDB, see Data\nModeling.\nThe concepts in this tutorial are applicable to all the\nlanguages\nsupported by FoundationDB. If you prefer, you can see a version of\nthis tutorial in\nJava,\nGo,\nPython\nor\nRuby.\nFirst steps\nLet's begin with \"Hello World.\"\nIf you have not yet installed FoundationDB, see Getting Started on\nmacOS\nor Getting Started on\nLinux.\nWe will start by importing the paths that we need from Rust standard\nlibrary, FDB and Tokio crates.\nuse fdb::transaction::{ReadTransaction, Transaction};\nuse fdb::tuple::Tuple;\n\nuse tokio::runtime::Runtime;\n\nuse std::env;\nuse std::error::Error;\n\nBefore using the API, we need to specify the API version. This allows\nprograms to maintain compatibility even if the API is modified in\nfuture versions. Next we open a FoundationDB database. The API will\nconnect to the FoundationDB cluster using the cluster file specified\nby FDB_CLUSTER_FILE. If you specify an empty path (\"\") to\nfdb::open_database\nthen the client will connect to the cluster as indicated by the\ndefault cluster\nfile.\nunsafe {\n fdb::select_api_version(710);\n fdb::start_network();\n}\n\nlet fdb_cluster_file = env::var(\"FDB_CLUSTER_FILE\").expect(\n \"FDB_CLUSTER_FILE not defined!\",\n);\n\nlet fdb_database = fdb::open_database(fdb_cluster_file)?;\n\nWe are ready to use the database. First, let us write a key-value\npair. We do this by executing a transaction with\nrun()\nmethod. We will also use methods on type\nTuple to\npack()\ndata for storage in the database.\nfdb_database\n .run(|tr| async move {\n tr.set(\n {\n let key_tup: (&'static str,) = (\"hello\",);\n let mut tup = Tuple::new();\n tup.add_string((key_tup.0).to_string());\n tup\n }\n .pack(),\n {\n let val_tup: (&'static str,) = (\"world\",);\n let mut tup = Tuple::new();\n tup.add_string((val_tup.0).to_string());\n tup\n }\n .pack(),\n );\n Ok(())\n })\n .await?;\n\nWhen run() returns without an error, the modification is durably\nstored in FoundationDB! This method creates a transaction with a\nsingle modification. We will see later how to do multiple operations\nin a single transaction. For now let us read back the data. We will\nuse Tuple again to unpack the result as a String.\nlet hello = fdb_database\n .run(|tr| async move {\n let result = tr\n .get(\n {\n let key_tup: (&'static str,) = (\"hello\",);\n let mut tup = Tuple::new();\n tup.add_string((key_tup.0).to_string());\n tup\n }\n .pack(),\n )\n .await?\n .unwrap();\n\n Ok(Tuple::from_bytes(result)?.get_string_ref(0)?.to_string())\n })\n .await?;\n\nprintln!(\"Hello {}\", hello);\n\nIf this is all working, it looks like we are ready to start building\nreal application. For reference, the full code for \"hello world\" is\nhere.\nClass scheduling application\nLet us say we have been asked to build a class scheduling system for\nstudents and administrators. We will walk through the design and\nimplementation of this application. Instead of typing everything in as\nyou follow along, look at\nclass-scheduling/src/main.rs\nfor a finished version of the program. You may want to refer to this\ncode as we walk through the tutorial.\nRequirements\nWe will need to let users list available classes and track which\nstudents have signed up for which classes. Here is a first cut of the\nfunctions we will need to implement.\navailable_classes() // returns a vector of classes\nsignup(student, class_name) // signs up a student for a class\ndropout(student, class_name) // drops a student from a class\n\nData model\nFirst, we need to design a data\nmodel. A\ndata model is just a method for storing our application data using\nkeys and values in FoundationDB. We seem to have two main types of\ndata.\n\n\nA list of classes (and)\n\n\nA record of which student will attend which classes\n\n\nLet us keep attending data like this:\n// (\"attends\", student, class_name) = \"\"\n\nWe will just store the key with a blank value to indicate that a\nstudent is signed up for a particular class. For this application, we\nare going to think about a key-value pair's key as a\ntuple. Encoding\na tuple of data elements into a key is a very common pattern for an\nordered key-value store.\nWe will keep data about classes like this:\n// (\"class\", class_name\") = seats_available\n\nSimilarly, each such key will represent an available class. We will\nuse seats_available to record the number of seats available.\nLeverage Rust type system\nIn FoundationDB keys and values are simple byte strings. The database\ndoes not interpret the contents of the keys and values. The tuple\nlayer provides some type safety, but that is still about\nrepresentation and not about the semantics of data. For example in\nour data model, student and class_name are tuple layer strings,\nbut semantically one refers to a student while the other refers to a\nclass name.\nIf we are not careful when writing our application, we could make the\nmistake of using student, when we intended to use class_name. As\nour data model becomes complex, it is easy to make mistakes.\nLuckily for us, we can leverage the Rust type system to avoid many\nsuch errors.\nBy using the\nnewtype\nidiom, we can get compile time guarantee that we would not be allowed\nto accidentally interchange a class_name value with a student\nvalue.\n#[derive(Clone, Debug, PartialEq)]\nstruct Class(String);\n\n#[derive(Clone, Debug, PartialEq)]\nstruct Student(String);\n\nWhen constructing and deconstructing FoundationDB tuples, we could\npotentially re-order the tuples. For example instead of\n// (\"attends\", student, class_name) = \"\"\n\nwe might mistakenly construct the following FoundationDB tuple, which\nwould break our data model.\n// (student, class_name, \"attends\") = \"\"\n\nWe can avoid this problems by creating custom types for keys and\nvalues. For an example see AttendsKey type in\nclass-scheduling/src/main.rs. Since\nRust tuple and\nFoundationDB tuple are isomorphic, within AttendsKey type, we can\nfirst construct a Rust tuple and then convert it to a FoundationDB\ntuple.\nlet key_tup: (&'static str, Student, Class) = \\\n (\"attends\", a.student, a.class_name);\n\nlet key_bytes = {\n let mut tup = Tuple::new();\n\n tup.add_string((key_tup.0).to_string());\n\n let Student(student_inner) = key_tup.1;\n tup.add_string(student_inner);\n\n let Class(class_inner) = key_tup.2;\n tup.add_string(class_inner);\n\n tup\n}\n.pack();\n\nHere we are asserting the type of key_tup to our data model and then\nimmediately creating the FoundationDB tuple in key_bytes. By keeping\nkey_tup and key_bytes visually next to each other, the scope for\nre-ordering errors is minimized.\nLastly, when we look at\nTransaction\nand\nReadTransaction\ntraits, we will find that many of the methods accepts values of type\nimpl Into<Key> and impl Into<Value>. We can take advantage of this\ndesign by implementing From trait on our types. Once we have the\nappropriate From traits implemented, these APIs will work with\nvalues of our type and there is no need to work with raw bytes.\nclass-scheduling/src/main.rs\nhas additional examples of above mentioned techniques.\nTransactions\nWe are going to rely on the powerful guarantees of transactions to\nhelp keep of all our modifications straight, so let us look at how the\nFoundationDB Tokio API lets you write a transaction function. We use\nrun() method to execute a code block transactionally. Let us write\nthe simple add_class function we will use to populate the database's\nclass list.\nfn add_class(tr: &FdbTransaction, class_name: Class) {\n // (\"class\", class_name)\n let class_key = ClassKey::new(class_name);\n\n let class_value = ClassValue::new(100);\n\n tr.set(class_key, class_value);\n}\n\ndb.run(|tr| async move {\n // Assuming we have initialized `class_name` with a value of type\n // `Class`\n add_class(&tr, class_name);\n\n Ok(())\n})\n.await\n\nThe run() method automatically creates a transaction and implements\na retry loop to ensure that the transaction eventually commits.\nThis is equivalent to something like:\nlet t = self.create_transaction()?;\n\nloop {\n let ret_val = (async move {\n // [...]\n\n // Assuming we have initialized `class_name` with a value of\n // type `Class`\n add_class(&t, class_name);\n\n Ok(())\n }).await;\n\n // Received an error\n if let Err(e) = ret_val {\n if FdbError::layer_error(e.code()) {\n // Check if it is a layer error. If so, just\n // return it.\n return Err(e);\n } else if let Err(e1) = unsafe { t.on_error(e) }.await {\n // Check if `on_error` returned an error. This\n // means we have a non-retryable error.\n return Err(e1);\n } else {\n continue;\n }\n }\n\n // No error. Attempt to commit the transaction.\n if let Err(e) = unsafe { t.commit() }.await {\n // Commit returned an error\n if let Err(e1) = unsafe { t.on_error(e) }.await {\n // Check if `on_error` returned an error. This\n // means we have a non-retryable error.\n return Err(e1);\n } else {\n continue;\n }\n }\n\n // Commit successful, return `Ok(())`\n return ret_val;\n}\n\n\nYou can abort a transaction by creating value Err(FdbError::new(err)\nwhere err is in the range 100.=999. This provides an unified\napproach to error handling in FoundationDB Tokio APIs. See\nerror module and\nFdbError\ntype documentation for details.\nNote that by default, the operation will be retried an infinite number\nof times and the transaction will never time out. It is therefore\nrecommended that the client choose a default transaction retry limit\nor timeout value that is suitable for their application. This can be\nset either at the transaction level by passing\nTransactionOption::RetryLimit\nand\nTransaction::Timeout\nto\nReadTransaction::set_option\nmethod or at the database level by passing\nDatabaseOption::TransactionRetryLimit\nand\nDatabaseOption::TransactionRetryLimit\nto\nFdbDatabase::set_option\nmethod. For example, one can set a one minute timeout on each transaction and a default retry limit of 100 by calling:\n// 60,000 ms = 1 minute\nfdb_database.set_option(DatabaseOption::TransactionTimeout(60000))?;\nfdb_database.set_option(DatabaseOption::TransactionRetryLimit(100))?;\n\nMaking some sample classes\nLet us make some sample classes and create a function\ninit_class_names that returns a vector of classes. We will make\nindividual classes from combinations of class types, levels and times:\nconst LEVELS: [&str; 9] = [\n \"intro\",\n \"for dummies\",\n \"remedial\",\n \"101\",\n \"201\",\n \"301\",\n \"mastery\",\n \"lab\",\n \"seminar\",\n];\n\nconst TYPES: [&str; 10] = [\n \"chem\", \"bio\", \"cs\", \"geometry\", \"calc\", \"alg\", \"film\", \"music\",\n \"art\", \"dance\",\n];\n\nconst TIMES: [&str; 18] = [\n \"2:00\", \"3:00\", \"4:00\", \"5:00\", \"6:00\", \"7:00\", \"8:00\", \"9:00\",\n \"10:00\", \"11:00\", \"12:00\", \"13:00\", \"14:00\", \"15:00\", \"16:00\",\n \"17:00\", \"18:00\", \"19:00\",\n];\n\nfn init_class_names() -> Vec<Class> {\n let mut class_names = Vec::new();\n\n for level in LEVELS {\n // we can't use type here as that is a keyword in Rust.\n for typ in TYPES {\n for time in TIMES {\n class_names.push(\n Class(\n format!(\"{} {} {}\", time, typ, level).to_string()\n )\n );\n }\n }\n }\n\n class_names\n}\n\nInitializing the database\nWe initialize the database with our class list:\nasync fn init(db: &FdbDatabase) -> FdbResult<()> {\n db.run(|tr| async move {\n // (\"attends\")\n let attends_prefix_range = AttendsPrefix::new().get_range();\n tr.clear_range(attends_prefix_range);\n\n // (\"class\")\n let class_prefix_range = ClassPrefix::new().get_range();\n tr.clear_range(class_prefix_range);\n\n for class_name in init_class_names() {\n add_class(&tr, class_name);\n }\n\n Ok(())\n })\n .await\n}\n\nAfter init() is run, the database will contain all the sample\nclasses we created above.\nListing available classes\nBefore students can do anything else, they need to be able to retrieve\na list of available classes from the database. We do this by\nimplementing available_classes function. Because FoundationDB sorts\nits data by key and therefore has efficient range-read capability, we\ncan retrieve all of the classes in a single database call. We find\nthis range of keys with\nget_range()\nmethod, which is called from\ninto_stream()\nmethod.\nconst KEY_CONVERTION_ERROR: i32 = 999;\n\nimpl TryFrom<Key> for ClassKey {\n type Error = FdbError;\n\n fn try_from(key: Key) -> FdbResult<ClassKey> {\n Tuple::from_bytes(key)\n .and_then(|tup| {\n // (\"class\", class_name)\n if tup.get_string_ref(0)?.as_str() != \"class\" {\n return Err(FdbError::new(KEY_CONVERTION_ERROR));\n }\n\n let class_name = Class(tup.get_string_ref(1)?.to_string());\n\n Ok(ClassKey::new(class_name))\n })\n .map_err(|_| FdbError::new(KEY_CONVERTION_ERROR))\n }\n}\n\nimpl ClassPrefix {\n fn get_range(&self) -> Range {\n // (\"class\")\n let class_tup: (&'static str,) = (\"class\",);\n\n let class_range = {\n let mut tup = Tuple::new();\n tup.add_string((class_tup.0).to_string());\n tup\n }\n .range(Bytes::new());\n\n class_range\n }\n}\n\nasync fn available_classes(tr: &FdbTransaction) -> FdbResult<Vec<Class>> {\n // (\"class\", ...)\n let mut class_range_stream = ClassPrefix::new()\n .get_range()\n .into_stream(tr, RangeOptions::default());\n\n let mut class_names = Vec::new();\n\n while let Some(x) = class_range_stream.next().await {\n let key = x?.into_key();\n let class_key = TryInto::<ClassKey>::try_into(key)?;\n class_names.push(class_key.into());\n }\n\n Ok(class_names)\n}\n\nIn general, the\nTuple::range()\nmethod returns a\nRange\nrepresenting all the key-value pairs starting with the specified\ntuple. In this case we want all classes, so we call Tuple::range()\nwith (\"class\",). Once we have the value of Range type, we can use\nRange::into_stream()\nto obtain a Tokio\nStream\nof the key-values contained within the range. To extract the class\nname, we unpack the key using\nTuple::fromBytes()\nand take its second part. (The first part is the prefix \"class\").\nSigning up for a class\nWe finally get to the crucial function. A student has decided on a\nclass (by name) and wants to sign up. The signup function will take\na student and a class_name.\nfn signup(tr: &FdbTransaction, student: Student, class_name: Class) {\n // (\"attends\", student, class_name)\n let attends_key = AttendsKey::new(student, class_name);\n\n // \"\"\n let attends_value = AttendsValue::new();\n\n tr.set(attends_key, attends_value);\n}\n\nWe simply insert the appropriate tuple key (with a blank value).\nDropping a class\nDropping a class is similar to signing up:\n// Unlike other bindings, we cannot name this function as `drop`,\n// because `drop` is already used in Rust.\nfn dropout(tr: &FdbTransaction, student: Student, class_name: Class) {\n // (\"attends\", student, class_name)\n let attends_key = AttendsKey::new(student, class_name);\n\n tr.clear(attends_key);\n}\n\nOf course, to actually drop the student from the class, we need to be\nable to delete a record from the database. We do this with the\nclear()\nmethod.\nDone?\nWe report back to the project leader that our application is done ---\nstudents can sign up for, drop, and list classes. Unfortunately, we\nlearn that a new problem has been discovered: popular classes are\nbeing over-subscribed. Our application now needs to enforce the class\nsize constraint as students add and drop classes.\nSeats are limited!\nLet us go back to the data model. Remember that we stored the number\nof seats in the class in the value of the key value entry in the class\nlist.\n// (\"class\", class_name\") = seats_available\n\nLet us refine that a bit to track the remaining number of seats in\nthe class. The initialization can work the same way (in our example,\nall classes initially have 100 seats), but the available_classes,\nsignup, and dropout functions are going to have to change. Let us\nstart with available_casses.\nasync fn available_classes(tr: &FdbTransaction) -> FdbResult<Vec<Class>> {\n // (\"class\", ...)\n let mut class_range_stream = ClassPrefix::new()\n .get_range()\n .into_stream(tr, RangeOptions::default());\n\n let mut class_names = Vec::new();\n\n while let Some(x) = class_range_stream.next().await {\n let (key, value) = x?.into_parts();\n\n let class_key = TryInto::<ClassKey>::try_into(key)?;\n\n let seats_available = ClassValue::from(value).get_val();\n\n if seats_available > 0 {\n class_names.push(class_key.into());\n }\n }\n\n Ok(class_names)\n}\n\nThis is easy --- we simply add a condition to check that the value is\nnon-zero. Let us check out signup next.\nconst NO_REMAINING_SEATS: i32 = 996;\nconst ALREADY_SIGNED_UP: i32 = 997;\n\nasync fn signup(\n tr: &FdbTransaction,\n student: Student,\n class_name: Class\n) -> FdbResult<()> {\n // (\"attends\", student, class_name)\n let attends_key = AttendsKey::new(student, class_name.clone());\n\n // \"\"\n let attends_value = AttendsValue::new();\n\n if tr.get(attends_key.clone()).await?.is_some() {\n Err(FdbError::new(ALREADY_SIGNED_UP))\n } else {\n // (\"class\", class_name)\n let class_key = ClassKey::new(class_name);\n\n // Safety: It is safe to `unwrap()` here because in our data\n // model assume that key `(\"class\", class_name)` will *always*\n // have seats left value.\n let class_value = ClassValue::from(\n tr.get(class_key.clone()).await?.unwrap()\n );\n\n let seats_left = class_value.get_val();\n\n if seats_left == 0 {\n Err(FdbError::new(NO_REMAINING_SEATS))\n } else {\n let updated_class_value = ClassValue::new(seats_left - 1);\n tr.set(class_key, updated_class_value);\n tr.set(attends_key, attends_value);\n Ok(())\n }\n }\n}\n\nWe now have to check that we are not already signed up, since we do\nnot want to double sign up to decrease the number of seats twice. Then\nwe look up how many seats are left to make sure there is a seat\nremaining so we do not push the counter into the negative. If there\nis a seat remaining, we decrement the counter.\nConcurrency and consistency\nThe signup function is starting to get a bit complex; it now reads\nand writes a few different key-value pairs in the database. One of the\ntricky issues in this situation is what happens as multiple\nclients/students read and modify the database at the same time. Could\ntwo students see one remaining seat and sign up at the same time?\nThese are tricky issues without simple answers --- unless you have\ntransactions! Because these functions are defined using FoundationDB\ntransactions, we can have a simple answer. Each transaction behaves as\nif it is the only one modifying the database. There is no way for a\ntransaction to \"see\" another transaction change the database, and each\ntransaction ensures that either all of its modifications occur or none\nof them do.\nLooking deeper, it is, of course, possible for two transactions to\nconflict. For example, if two people both see a class with one seat\nand sign up at the same time, FoundationDB must allow only one to\nsucceed. This causes one of the transactions to fail to commit (which\ncan also be caused by network outages, crashes, etc.). To ensure\ncorrect operation, applications need to handle this situation, usually\nvia retrying the transaction. In this case, the conflicting\ntransaction will be retried automatically by the run() method and\nwill eventually lead to the correct result, a NO_REMAINING_SEATS\nerror.\nIdempotence\nOccasionally, a transaction might be retried even after it succeeds\n(for example, if the client loses contact with the cluster at just the\nwrong moment). This can cause problems if transactions are not written\nto be idempotent, i.e. to have the same effect if committed twice as if\ncommitted once. There are generic design patterns for making any\ntransaction\nidempotent,\nbut many transactions are naturally idempotent. For example, all of the\ntransactions in this tutorial are idempotent.\nDropping with limited seats\nLet us finish up the limited seats feature by modifying the dropout\nfunction.\nasync fn dropout(\n tr: &FdbTransaction,\n student: Student,\n class_name: Class\n) -> FdbResult<()> {\n // (\"attends\", student, class_name)\n let attends_key = AttendsKey::new(student, class_name.clone());\n\n if tr.get(attends_key.clone()).await?.is_none() {\n // not taking class\n Ok(())\n } else {\n // (\"class\", class_name)\n let class_key = ClassKey::new(class_name);\n\n // Safety: It is safe to `unwrap()` here because in our data\n // model assume that key `(\"class\", class_name)` will *always*\n // have seats left value.\n let class_value = ClassValue::from(\n tr.get(class_key.clone()).await?.unwrap()\n );\n let seats_left = class_value.get_val();\n let updated_class_value = ClassValue::new(seats_left + 1);\n tr.set(class_key, updated_class_value);\n tr.clear(attends_key);\n\t\n Ok(())\n }\n}\n\nThis case is easier than signup because there are no constraints we\ncan hit. We just need to make sure the student is in the class and to\n\"give back\" one seat when the student drops.\nMore features?!\nOf course, as soon as our new version of the system goes live, we hear\nof a trick that certain students are using. They are signing up for\nall classes immediately, and only later dropping those that they do\nnot want to take. This as lead to an unusable system, and we have been\nasked to fix it. We decide to limit students to five classes:\nconst TOO_MANY_CLASSES: i32 = 995;\n\nasync fn signup(\n tr: &FdbTransaction,\n student: Student,\n class_name: Class\n) -> FdbResult<()> {\n // (\"attends\", student, class_name)\n let attends_key = AttendsKey::new(student.clone(), class_name.clone());\n\n // \"\"\n let attends_value = AttendsValue::new();\n\n if tr.get(attends_key.clone()).await?.is_some() {\n Err(FdbError::new(ALREADY_SIGNED_UP))\n } else {\n // (\"class\", class_name)\n let class_key = ClassKey::new(class_name);\n\n // Safety: It is safe to `unwrap()` here because in our data\n // model assume that key `(\"class\", class_name)` will *always*\n // have seats left value.\n let class_value = ClassValue::from(\n tr.get(class_key.clone()).await?.unwrap()\n );\n\n let seats_left = class_value.get_val();\n\n if seats_left == 0 {\n Err(FdbError::new(NO_REMAINING_SEATS))\n } else {\n let attends_student_kvs =\n get_attends_student_keyvalue(tr, student).await?;\n\n if attends_student_kvs.len() == 5 {\n Err(FdbError::new(TOO_MANY_CLASSES))\n } else {\n let updated_class_value = ClassValue::new(seats_left - 1);\n tr.set(class_key, updated_class_value);\n tr.set(attends_key, attends_value);\n Ok(())\n }\n }\n }\n}\n\nFortunately, we decided on a data model that keeps all of the\nattending records for a single student together. With this approach,\nwe can use a single range read to retrieve all the classes that a\nstudent attends. We return an error if the number of classes has\nreached the limit of five.\nComposing transactions\nOh, just one last feature, we are told. We have students that are\ntrying to switch from one popular class to another. By the time they\ndrop one class to free up a slot for themselves, the open slot in the\nother class is gone. By the time they see this and try to re-add their\nold class, that slot is gone too! So, can we make it so that a student\ncan switch from one class to another without this worry?\nFortunately, we have FoundationDB, and this sounds an awful lot like\nthe transactional property of atomicity --- the all-or-nothing\nbehavior that we rely on. All we need to do is compose the dropout\nand signup function into new switch_classes function. This make\nthe switch_classes function exceptionally easy:\n#[derive(Clone, Debug)]\nstruct OldClass(Class);\n\n#[derive(Clone, Debug)]\nstruct NewClass(Class);\n\nasync fn switch_classes(\n tr: &FdbTransaction,\n student: Student,\n old_class: OldClass,\n new_class: NewClass,\n) -> FdbResult<()> {\n let old_attends_key = AttendsKey::new(student.clone(), {\n let OldClass(class_name) = old_class.clone();\n class_name\n });\n let new_attends_key = AttendsKey::new(student.clone(), {\n let NewClass(class_name) = new_class.clone();\n class_name\n });\n if tr.get(old_attends_key).await?.is_some() &&\n tr.get(new_attends_key).await?.is_some() {\n // nothing to switch\n Ok(())\n } else {\n // switching classes\n dropout(tr, student.clone(), {\n let OldClass(class_name) = old_class;\n class_name\n })\n .await?;\n signup(tr, student.clone(), {\n let NewClass(class_name) = new_class;\n class_name\n })\n .await?;\n Ok(())\n }\n}\n\nThe simplicity of this implementation belies the sophistication of\nwhat FoundationDB is taking care for us.\nBy dropping the old class and signing up for the new one inside a\nsingle transaction, we ensure either both steps happen, or that\nneither happens. The first notable thing about switch_classes\nfunction is that it is transactional, but it also calls the\ntransactional functions signup and dropout. Once a transaction is\ncreated and passed in as tr, the calls to dropout and signup\nboth share the same tr. This ensures that they see each other's\nmodifications to the database, and all of the changes that both of\nthem make in sequence are made transactionally when the\nswitch_classes function returns. This compositional capability is\nvery powerful.\nAlso note that, if an error occurs, for example in signup, and the\nerror is not handled in switch_classes, then the error be propagated\nto the calling function. Eventually it will reach the run() where we\ncheck if the error is a retryable error. If it is not, then\ntransaction value is dropped, automatically rolling back all database\nmodifications, leaving the database completely unchanged by the\nhalf-executed function.\nAre we done?\nYep, we're done and ready to deploy. If you want to see this entire\napplication in one place plus some testing code using Tokio tasks to\nsimulate concurrency, look at\nclass-scheduling/src/main.rs.\nDeploying and scaling\nSince we store all state for this application in FoundationDB,\ndeploying and scaling this solution up is impressively painless. Just\nrun a web server, the UI, this back end, and point the whole thing at\nFoundationDB. We can run as many computers with this setup as we want,\nand they can all hit the database at the same time because of the\ntransactional integrity of FoundationDB. Also, since all of the state\nin the system is stored in the database, any of these computers can\nfail without any lasting consequences.\nNext steps\n\nSee Data\nModeling\nfor guidance on using tuples and subspaces to enable effective\nstorage and retrieval of data.\nSee Developer\nGuide\nfor general guidance on development using FoundationDB.\n\n","id":"https://fdb-rs.github.io/docs/crate-fdb/class-scheduling-tutorial/","title":"Class Scheduling Tutorial"},"https://fdb-rs.github.io/docs/crate-fdb/client-network-thread/":{"body":"Full working code for concepts described in this section is\nhere.\nFoundationDB clients are required to start a network\nthread\nbefore they can communicate with the cluster.\nEach language binding provides its own mechanism for starting client\nnetwork thread. An important consideration is that while the client\nnetwork thread can be started and stopped, once it has been stopped,\nit cannot be started again.\nFor our Tokio binding, we recommend that you start the client network\nthread and open the database in the main thread before starting the\nTokio runtime. Once the Tokio runtime completes, you can safely close\nthe database and stop the network thread.\nIn the next sections we describe how this can be accomplished in more\ndetail.\nIdentifying the cluster file\nBegin by identifying the location of the FoundationDB cluster\nfile. It\nis common practice to specify this file using the environment variable\nFDB_CLUSTER_FILE.\nlet fdb_cluster_file = env::var(\"FDB_CLUSTER_FILE\")\n .expect(\"FDB_CLUSTER_FILE not defined!\");\n\nSelect API version\nBefore starting the client network you need to specify API\nversion\nto use. This can be done as follows.\nunsafe {\n fdb::select_api_version(710);\n // ...\n}\n\nHere we are selecting API version 710. In Rust unsafe keyword is\nused to indicate to the user of API that there invariants that cannot\nbe checked by the compiler.\nFor our bindings, we have marked initialization APIs as unsafe\nprimarily to help you understand the interaction that between Tokio\nruntime and FoundationDB client network thread.\nStart Client Network Thread\nOnce the API version is selected you can start the client network\nthread as follows.\nunsafe {\n fdb::select_api_version(710);\n fdb::start_network();\n}\n\nOpen Database\nAfter the client network thread as started, you can open the\nFoundationDB database specified by the cluster file.\nlet fdb_database = fdb::open_database(fdb_cluster_file)?;\n\nopen_database\nfunction returns a value of\nFdbResult\ntype.\nFdbResult type provides a common error handling abstraction for all\nAPIs in the crate. In addition it also signals\nerrors\nthat might have occurred in the C API.\nIn the above code fdb_database is a value of\nFdbDatabase\ntype and points to the FoundationDB database specified by the cluster\nfile. \nStart Tokio Runtime\nAfter you have obtained a value of FdbDatabase type, you can start\nthe Tokio Runtime, its the main async task and move a cloned value\nof FdbDatabase into the main Tokio task.\nlet rt = Runtime::new()?;\n\nlet cloned_fdb_database = fdb_database.clone();\n\nrt.block_on(async {\n let fdb_database = cloned_fdb_database;\n\n // your main async app here\n \n Result::<(), Box<dyn Error>>::Ok(())\n})?;\n\nAt this point, rt.block_on will block the main thread. In your\napplication you will have multiple running threads. They would include\nthreads launched by Tokio runtime and FoundationDB client network\nthread.\nStop Client Network Thread\nOnce rt.block_on returns, you can gracefully stop the client network\nthread by doing the following.\ndrop(fdb_database);\n\nunsafe {\n fdb::stop_network();\n}\n\nThis should allow you to cleanly exit your application.\n","id":"https://fdb-rs.github.io/docs/crate-fdb/client-network-thread/","title":"Client Network Thread"},"https://fdb-rs.github.io/docs/crate-fdb/linking/":{"body":"Full working code for concepts described in this section is\nhere.\nBegin by adding fdb crate as a\ndependency in your Cargo.toml file.\n[dependencies]\nfdb = \"0.x\"\n\nfdb crate supports\nlinking\nwith different versions of the C library using cargo feature\nflags. In order to\ncorrectly build your application, you are required to specify the\nversion of the C library to link against. This can be done in two\nways. Either by using the command line option --features fdb/fdb-X_Y or\nby specifying the following in your Cargo.toml. Here X is the\nmajor version and Y is the minor version of FoundationDB.\n[features]\ndefault = [\"fdb/fdb-X_Y\"]\n\nIf you have installed libfdb_c.so in a non-standard location, you\ncan use the environment variable\nRUSTC_LINK_SEARCH_FDB_CLIENT_LIB\nto specify the location of the C library.\nNote While it is required for your application to link to a\nspecific version of fdb_c library during build time, FoundationDB\nclient can also dynamically load newer version during runtime. This\nfeature is used during cluster upgrades. See this\nlink\nfor details.\n","id":"https://fdb-rs.github.io/docs/crate-fdb/linking/","title":"Linking with C library"},"https://fdb-rs.github.io/docs/crate-fdb/prerequisites/":{"body":"Before starting please familiarize yourself with the following.\nTokio\nTokio project provides an excellent tutorial that you can find\nhere. If you are new to Tokio, we\nurge to complete the tutorial.\nFoundationDB\nFoundationDB comes with extensive documentation. If you are new to\nFoundationDB please read through the following sections of\nFoundationDB documentation.\n\n\nWhy FoundationDB\n\n\nLayer Concept\n\n\nFeatures\n\n\nAnti-Features\n\n\nGetting Started on Linux or Getting Started on macOS\n\n\nUsing FoundationDB Clients\n\n\nDeveloper Guide\nYou can ignore the\ndirectories\nsection. We do not support directory layer in our API. Instead we\nsupport FoundationDB 7.1\nTenants that\nnatively provides similar feature.\nWhen you read the section on transaction retry\nloop\ntake note of the presence of two distinct types - A database type\nand a transaction type. Other language bindings allows values of\nthese two types to be used interchangeably in their API. In our\nbindings, we keep distinction between a value of database type and\nvalue of transaction type separate. You will see this come up in the\nclass scheduling tutorial.\n\n\nPython Class Scheduling Tutorial\nEven though you might not use Python in production, this tutorial\nwill help you become familiar with the API. You can find our version\nof class scheduling tutorial here.\n\n\n","id":"https://fdb-rs.github.io/docs/crate-fdb/prerequisites/","title":"Prerequisites"},"https://fdb-rs.github.io/docs/getting-started/":{"body":"","id":"https://fdb-rs.github.io/docs/getting-started/","title":"Getting Started"},"https://fdb-rs.github.io/docs/getting-started/introduction/":{"body":"Each crate comes with reference documentation that you will find on\ndocs.rs page for that crate. Here we provide you\nwith guide level material.\nIf you have questions, please contact us and\nwe will be happy to help.\nfdb is our first crate. We recommend starting your FoundationDB plus\nTokio journey with this crate.\n","id":"https://fdb-rs.github.io/docs/getting-started/introduction/","title":"Introduction"},"https://fdb-rs.github.io/docs/help/":{"body":"","id":"https://fdb-rs.github.io/docs/help/","title":"Help"},"https://fdb-rs.github.io/docs/help/code-of-conduct/":{"body":"We follow FoundationDB and Tokio Code of Conduct.\n\nFoundationDB Code of Conduct\nTokio Code of Conduct\n\n","id":"https://fdb-rs.github.io/docs/help/code-of-conduct/","title":"Code of Conduct"},"https://fdb-rs.github.io/docs/help/contact-us/":{"body":"Thank you for your interest in the fdb-rs Project crates.\nIf your question is related to a particular fdb-rs crate, then please\nraise a GitHub Issue in the GitHub repository of that crate. \nFor other questions please use FoundationDB\nForums.\n","id":"https://fdb-rs.github.io/docs/help/contact-us/","title":"Contact Us"},"https://fdb-rs.github.io/privacy-policy/":{"body":"From fdb-rs GitHub organization, we do not collect any personal\ndata. This website is hosted on GitHub\nPages. Therefore you are also subject to\nGitHub Site\nPolicy.\n","id":"https://fdb-rs.github.io/privacy-policy/","title":"Privacy Policy"}},"docInfo":{"https://fdb-rs.github.io/":{"body":0,"title":2},"https://fdb-rs.github.io/authors/":{"body":3,"title":1},"https://fdb-rs.github.io/authors/rajivr/":{"body":4,"title":3},"https://fdb-rs.github.io/blog/":{"body":0,"title":1},"https://fdb-rs.github.io/blog/fdb-crate-3-0-1/":{"body":200,"title":4},"https://fdb-rs.github.io/blog/introducing-fdb-crate/":{"body":269,"title":5},"https://fdb-rs.github.io/docs/":{"body":0,"title":1},"https://fdb-rs.github.io/docs/crate-fdb/":{"body":0,"title":2},"https://fdb-rs.github.io/docs/crate-fdb/class-scheduling-tutorial/":{"body":2098,"title":3},"https://fdb-rs.github.io/docs/crate-fdb/client-network-thread/":{"body":271,"title":3},"https://fdb-rs.github.io/docs/crate-fdb/linking/":{"body":105,"title":3},"https://fdb-rs.github.io/docs/crate-fdb/prerequisites/":{"body":127,"title":1},"https://fdb-rs.github.io/docs/getting-started/":{"body":0,"title":2},"https://fdb-rs.github.io/docs/getting-started/introduction/":{"body":29,"title":1},"https://fdb-rs.github.io/docs/help/":{"body":0,"title":1},"https://fdb-rs.github.io/docs/help/code-of-conduct/":{"body":11,"title":2},"https://fdb-rs.github.io/docs/help/contact-us/":{"body":24,"title":1},"https://fdb-rs.github.io/privacy-policy/":{"body":16,"title":2}},"length":18},"lang":"English"};