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</div> + <div id="bodyColumn" > +<div class="section"> +<h2><a name="Search"></a>Search</h2> +<p>Atlas exposes search over the metadata in two ways:</p> +<ul> +<li>Basic Search</li> +<li>Advanced Search (DSL or Full-Text)</li></ul></div> +<div class="section"> +<h3><a name="Basic_search"></a>Basic search</h3> +<p>The basic search allows you to query using typename of an entity, associated classification/tag and has support for filtering on the entity attribute(s) as well as the classification/tag attributes.</p> +<p>The entire query structure can be represented using the following JSON structure (called SearchParameters)</p> +<div class="source"><pre class="prettyprint"> +{ + "typeName": "hive_table", + "excludeDeletedEntities": true, + "classification" : "", + "query": "", + "limit": 25, + "offset": 0, + "entityFilters": { + "attributeName": "name", + "operator": "contains", + "attributeValue": "testtable" + }, + "tagFilters": null, + "attributes": [""] +} + +</pre></div> +<p><b><i>Field description</i></b></p> +<p></p> +<ul> +<li>typeName: The type of entity to look for</li> +<li>excludeDeletedEntities: Should the search include deleted entities too (default: true)</li> +<li>classification: Only include entities with given Classification/tag</li> +<li>query: Any free text occurrence that the entity should have (generic/wildcard queries might be slow)</li> +<li>limit: Max number of results to fetch</li> +<li>offset: Starting offset of the result set (useful for pagination)</li> +<li>entityFilters: Entity Attribute filter(s)</li> +<li>tagFilters: Classification/tag Attribute filter(s)</li> +<li>attributes: Attributes to include in the search result (default: include any attribute present in the filter)</li></ul> +<p>Attribute based filtering can be done on multiple attributes with AND/OR condition.</p> +<p><b>NOTE: The tagFilters and entityFilters field have same JSON structure.</b></p> +<p><b><i>Examples of filtering (for hive_table attributes)</i></b></p> +<ul> +<li>Single attribute</li></ul> +<div class="source"><pre class="prettyprint"> + { + "typeName": "hive_table", + "excludeDeletedEntities": true, + "classification" : "", + "query": "", + "limit": 50, + "offset": 0, + "entityFilters": { + "attributeName": "name", + "operator": "contains", + "attributeValue": "testtable" + }, + "tagFilters": null, + "attributes": [""] + } + +</pre></div> +<p></p> +<ul> +<li>Multi-attribute with OR</li></ul> +<div class="source"><pre class="prettyprint"> + { + "typeName": "hive_table", + "excludeDeletedEntities": true, + "classification" : "", + "query": "", + "limit": 50, + "offset": 0, + "entityFilters": { + "condition": "OR", + "criterion": [ + { + "attributeName": "name", + "operator": "contains", + "attributeValue": "testtable" + }, + { + "attributeName": "owner", + "operator": "eq", + "attributeValue": "admin" + } + ] + }, + "tagFilters": null, + "attributes": [""] + } + +</pre></div> +<p></p> +<ul> +<li>Multi-attribute with AND</li></ul> +<div class="source"><pre class="prettyprint"> + { + "typeName": "hive_table", + "excludeDeletedEntities": true, + "classification" : "", + "query": "", + "limit": 50, + "offset": 0, + "entityFilters": { + "condition": "AND", + "criterion": [ + { + "attributeName": "name", + "operator": "contains", + "attributeValue": "testtable" + }, + { + "attributeName": "owner", + "operator": "eq", + "attributeValue": "admin" + } + ] + }, + "tagFilters": null, + "attributes": [""] + } + +</pre></div> +<p><b><i>Supported operators for filtering</i></b></p> +<p></p> +<ul> +<li>LT (symbols: <, lt) works with Numeric, Date attributes</li> +<li>GT (symbols: >, gt) works with Numeric, Date attributes</li> +<li>LTE (symbols: <=, lte) works with Numeric, Date attributes</li> +<li>GTE (symbols: >=, gte) works with Numeric, Date attributes</li> +<li>EQ (symbols: eq, =) works with Numeric, Date, String attributes</li> +<li>NEQ (symbols: neq, !=) works with Numeric, Date, String attributes</li> +<li>LIKE (symbols: like, LIKE) works with String attributes</li> +<li>STARTS_WITH (symbols: startsWith, STARTSWITH) works with String attributes</li> +<li>ENDS_WITH (symbols: endsWith, ENDSWITH) works with String attributes</li> +<li>CONTAINS (symbols: contains, CONTAINS) works with String attributes</li></ul> +<p><b><i>CURL Samples</i></b></p> +<div class="source"><pre class="prettyprint"> + curl -sivk -g + -u <user>:<password> + -X POST + -d '{ + "typeName": "hive_table", + "excludeDeletedEntities": true, + "classification" : "", + "query": "", + "limit": 50, + "offset": 0, + "entityFilters": { + "condition": "AND", + "criterion": [ + { + "attributeName": "name", + "operator": "contains", + "attributeValue": "testtable" + }, + { + "attributeName": "owner", + "operator": "eq", + "attributeValue": "admin" + } + ] + }, + "tagFilters": null, + "attributes": [""] + }' + <protocol>://<atlas_host>:<atlas_port>/api/atlas/v2/search/basic + +</pre></div></div> +<div class="section"> +<h3><a name="Advanced_Search"></a>Advanced Search</h3></div> +<div class="section"> +<h4><a name="Search_DSL_Grammar"></a>Search DSL Grammar</h4> +<p>The DSL exposes an SQL like query language for searching the metadata based on the type system. The grammar for the DSL is below.</p> +<div class="source"><pre class="prettyprint"> +queryWithPath: query ~ opt(WITHPATH) + +query: querySrc ~ opt(loopExpression) ~ opt(groupByExpr) ~ opt(selectClause) ~ opt(orderby) ~ opt(limitOffset) + +querySrc: rep1sep(singleQrySrc, opt(COMMA)) + +singleQrySrc = FROM ~ fromSrc ~ opt(WHERE) ~ opt(expr ^? notIdExpression) | + WHERE ~ (expr ^? notIdExpression) | + expr ^? notIdExpression | + fromSrc ~ opt(WHERE) ~ opt(expr ^? notIdExpression) + +fromSrc: identifier ~ AS ~ alias | identifier + +groupByExpr = GROUPBY ~ (LPAREN ~> rep1sep(selectExpression, COMMA) <~ RPAREN) + +orderby: ORDERBY ~ expr ~ opt (sortOrder) + +limitOffset: LIMIT ~ lmt ~ opt (offset) + +offset: OFFSET ~ offsetValue + +sortOrder = ASC | DESC + +loopExpression: LOOP ~ (LPAREN ~> query <~ RPAREN) ~ opt(intConstant <~ TIMES) ~ opt(AS ~> alias) + +selectClause: SELECT ~ rep1sep(selectExpression, COMMA) + +countClause = COUNT ~ LPAREN ~ RPAREN + +maxClause = MAX ~ (LPAREN ~> expr <~ RPAREN) + +minClause = MIN ~ (LPAREN ~> expr <~ RPAREN) + +sumClause = SUM ~ (LPAREN ~> expr <~ RPAREN) + +selectExpression: expr ~ opt(AS ~> alias) + +expr: compE ~ opt(rep(exprRight)) + +exprRight: (AND | OR) ~ compE + +compE: + arithE ~ (LT | LTE | EQ | NEQ | GT | GTE) ~ arithE | + arithE ~ (ISA | IS) ~ ident | + arithE ~ HAS ~ ident | + arithE | countClause | maxClause | minClause | sumClause + +arithE: multiE ~ opt(rep(arithERight)) + +arithERight: (PLUS | MINUS) ~ multiE + +multiE: atomE ~ opt(rep(multiERight)) + +multiERight: (STAR | DIV) ~ atomE + +atomE: literal | identifier | LPAREN ~> expr <~ RPAREN + +identifier: rep1sep(ident, DOT) + +alias: ident | stringLit + +literal: booleanConstant | + intConstant | + longConstant | + floatConstant | + doubleConstant | + stringLit + +</pre></div> +<p>Grammar language: {noformat} opt(a) => a is optional ~ => a combinator. 'a ~ b' means a followed by b rep => zero or more rep1sep => one or more, separated by second arg. {noformat}</p> +<p>Language Notes:</p> +<ul> +<li>A <b>SingleQuery</b> expression can be used to search for entities of a <i>Trait</i> or <i>Class</i>.</li></ul>Entities can be filtered based on a 'Where Clause' and Entity Attributes can be retrieved based on a 'Select Clause'. +<ul> +<li>An Entity Graph can be traversed/joined by combining one or more SingleQueries.</li> +<li>An attempt is made to make the expressions look SQL like by accepting keywords "SELECT",</li></ul>"FROM", and "WHERE"; but these are optional and users can simply think in terms of Entity Graph Traversals. +<ul> +<li>The transitive closure of an Entity relationship can be expressed via the <i>Loop</i> expression. A</li></ul><i>Loop</i> expression can be any traversal (recursively a query) that represents a <i>Path</i> that ends in an Entity of the same <i>Type</i> as the starting Entity. +<ul> +<li>The <i>WithPath</i> clause can be used with transitive closure queries to retrieve the Path that</li></ul>connects the two related Entities. (We also provide a higher level interface for Closure Queries see scaladoc for 'org.apache.atlas.query.ClosureQuery') +<ul> +<li>GROUPBY is optional. Group by can be specified with aggregate methods like max, min, sum and count. When group by is specified aggregated results are returned based on the method specified in select clause. Select expression is mandatory with group by expression.</li> +<li>ORDERBY is optional. When order by clause is specified, case insensitive sorting is done based on the column specified.</li></ul>For sorting in descending order specify 'DESC' after order by clause. If no order by is specified, then no default sorting is applied. +<ul> +<li>LIMIT is optional. It limits the maximum number of objects to be fetched starting from specified optional offset. If no offset is specified count starts from beginning.</li> +<li>There are couple of Predicate functions different from SQL:</li></ul>* <i>is</i> or <i>isa</i>can be used to filter Entities that have a particular Trait. * <i>has</i> can be used to filter Entities that have a value for a particular Attribute. +<ul> +<li>Any identifiers or constants with special characters(space,$,",{,}) should be enclosed within backquote (`)</li></ul></div> +<div class="section"> +<h5><a name="DSL_Examples"></a>DSL Examples</h5> +<p>For the model, Asset - attributes name, owner, description DB - supertype Asset - attributes clusterName, parameters, comment Column - extends Asset - attributes type, comment Table - supertype Asset - db, columns, parameters, comment Traits - PII, Log Data</p> +<p>DSL queries: * from DB</p> +<ul> +<li>DB where name="Reporting" select name, owner</li> +<li>DB where name="Reporting" select name, owner orderby name</li> +<li>DB where name="Reporting" select name limit 10</li> +<li>DB where name="Reporting" select name, owner limit 10 offset 0</li> +<li>DB where name="Reporting" select name, owner orderby name limit 10 offset 5</li> +<li>DB where name="Reporting" select name, owner orderby name desc limit 10 offset 5</li> +<li>DB has name</li> +<li>DB is JdbcAccess</li> +<li>Column where Column isa PII</li> +<li>Table where name="sales_fact", columns</li> +<li>Table where name="sales_fact", columns as column select column.name, column.dataType, column.comment</li> +<li>DB groupby(owner) select owner, count()</li> +<li>DB groupby(owner) select owner, max(name)</li> +<li>DB groupby(owner) select owner, min(name)</li> +<li>from Person select count() as 'count', max(Person.age) as 'max', min(Person.age)</li> +<li>`Log Data`</li></ul></div> +<div class="section"> +<h4><a name="Full-text_Search"></a>Full-text Search</h4> +<p>Atlas also exposes a lucene style full-text search capability.</p></div> + </div> + </div> + <hr/> + <footer> + <div class="container"> + <div class="row"> +Copyright ̩ 2018 The Apache Software Foundation, Licensed under the Apache License, Version 2.0. + </div> + <p id="poweredBy" class="pull-right"><a href="http://maven.apache.org/"; title="Built by Maven" class="poweredBy"><img class="builtBy" alt="Built by Maven" src="./images/logos/maven-feather.png" /></a> +</p> + </div> + </footer> + </body> +</html>
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Storm makes it easy to reliably process unbounded streams of data, doing for real-time processing what Hadoop did for batch processing. The process is essentially a DAG of nodes, which is called <b>topology</b>.</p> +<p>Apache Atlas is a metadata repository that enables end-to-end data lineage, search and associate business classification.</p> +<p>The goal of this integration is to push the operational topology metadata along with the underlying data source(s), target(s), derivation processes and any available business context so Atlas can capture the lineage for this topology.</p> +<p>There are 2 parts in this process detailed below:</p> +<ul> +<li>Data model to represent the concepts in Storm</li> +<li>Storm Atlas Hook to update metadata in Atlas</li></ul></div> +<div class="section"> +<h3><a name="Storm_Data_Model"></a>Storm Data Model</h3> +<p>A data model is represented as Types in Atlas. It contains the descriptions of various nodes in the topology graph, such as spouts and bolts and the corresponding producer and consumer types.</p> +<p>The following types are added in Atlas.</p> +<p></p> +<ul> +<li>storm_topology - represents the coarse-grained topology. A storm_topology derives from an Atlas Process type and hence can be used to inform Atlas about lineage.</li> +<li>Following data sets are added - kafka_topic, jms_topic, hbase_table, hdfs_data_set. These all derive from an Atlas Dataset type and hence form the end points of a lineage graph.</li> +<li>storm_spout - Data Producer having outputs, typically Kafka, JMS</li> +<li>storm_bolt - Data Consumer having inputs and outputs, typically Hive, HBase, HDFS, etc.</li></ul> +<p>The Storm Atlas hook auto registers dependent models like the Hive data model if it finds that these are not known to the Atlas server.</p> +<p>The data model for each of the types is described in the class definition at org.apache.atlas.storm.model.StormDataModel.</p></div> +<div class="section"> +<h3><a name="Storm_Atlas_Hook"></a>Storm Atlas Hook</h3> +<p>Atlas is notified when a new topology is registered successfully in Storm. Storm provides a hook, backtype.storm.ISubmitterHook, at the Storm client used to submit a storm topology.</p> +<p>The Storm Atlas hook intercepts the hook post execution and extracts the metadata from the topology and updates Atlas using the types defined. Atlas implements the Storm client hook interface in org.apache.atlas.storm.hook.StormAtlasHook.</p></div> +<div class="section"> +<h3><a name="Limitations"></a>Limitations</h3> +<p>The following apply for the first version of the integration.</p> +<p></p> +<ul> +<li>Only new topology submissions are registered with Atlas, any lifecycle changes are not reflected in Atlas.</li> +<li>The Atlas server needs to be online when a Storm topology is submitted for the metadata to be captured.</li> +<li>The Hook currently does not support capturing lineage for custom spouts and bolts.</li></ul></div> +<div class="section"> +<h3><a name="Installation"></a>Installation</h3> +<p>The Storm Atlas Hook needs to be manually installed in Storm on the client side. The hook artifacts are available at: $ATLAS_PACKAGE/hook/storm</p> +<p>Storm Atlas hook jars need to be copied to $STORM_HOME/extlib. Replace STORM_HOME with storm installation path.</p> +<p>Restart all daemons after you have installed the atlas hook into Storm.</p></div> +<div class="section"> +<h3><a name="Configuration"></a>Configuration</h3></div> +<div class="section"> +<h4><a name="Storm_Configuration"></a>Storm Configuration</h4> +<p>The Storm Atlas Hook needs to be configured in Storm client config in <b>$STORM_HOME/conf/storm.yaml</b> as:</p> +<div class="source"><pre class="prettyprint"> +storm.topology.submission.notifier.plugin.class: "org.apache.atlas.storm.hook.StormAtlasHook" + +</pre></div> +<p>Also set a 'cluster name' that would be used as a namespace for objects registered in Atlas. This name would be used for namespacing the Storm topology, spouts and bolts.</p> +<p>The other objects like data sets should ideally be identified with the cluster name of the components that generate them. For e.g. Hive tables and databases should be identified using the cluster name set in Hive. The Storm Atlas hook will pick this up if the Hive configuration is available in the Storm topology jar that is submitted on the client and the cluster name is defined there. This happens similarly for HBase data sets. In case this configuration is not available, the cluster name set in the Storm configuration will be used.</p> +<div class="source"><pre class="prettyprint"> +atlas.cluster.name: "cluster_name" + +</pre></div> +<p>In <b>$STORM_HOME/conf/storm_env.ini</b>, set an environment variable as follows:</p> +<div class="source"><pre class="prettyprint"> +STORM_JAR_JVM_OPTS:"-Datlas.conf=$ATLAS_HOME/conf/" + +</pre></div> +<p>where ATLAS_HOME is pointing to where ATLAS is installed.</p> +<p>You could also set this up programatically in Storm Config as:</p> +<div class="source"><pre class="prettyprint"> + Config stormConf = new Config(); + ... + stormConf.put(Config.STORM_TOPOLOGY_SUBMISSION_NOTIFIER_PLUGIN, + org.apache.atlas.storm.hook.StormAtlasHook.class.getName()); + +</pre></div></div> + </div> + </div> + <hr/> + <footer> + <div class="container"> + <div class="row"> +Copyright é 2018 The Apache Software Foundation, Licensed under the Apache License, Version 2.0. + </div> + <p id="poweredBy" class="pull-right"><a href="http://maven.apache.org/"; 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data-size="medium" width="60px" align="right" ></div> + </li></ul> + </div> + </div> + </div> + </div> + <div class="container"> + <div id="banner"> + <div class="pull-left"><a href=".." id="bannerLeft"><img src="images/atlas-logo.png" alt="Apache Atlas" width="200px" height="45px"/></a></div> + <div class="pull-right"></div> + <div class="clear"><hr/></div> + </div> + + <div id="breadcrumbs"> + <ul class="breadcrumb"> + <li class=""><a href="http://www.apache.org"; class="externalLink" title="Apache">Apache</a><span class="divider">/</span></li> + <li class=""><a href="index.html" title="Atlas">Atlas</a><span class="divider">/</span></li> + <li class="active ">Type System</li> + <li id="publishDate" class="pull-right"><span class="divider">|</span> Last Published: 2018-01-25</li> + <li id="projectVersion" class="pull-right">Version: 1.0.0-alpha</li> + </ul> + </div> + <div id="bodyColumn" > +<div class="section"> +<h2><a name="Type_System"></a>Type System</h2></div> +<div class="section"> +<h3><a name="Overview"></a>Overview</h3> +<p>Atlas allows users to define a model for the metadata objects they want to manage. The model is composed of definitions called ‘types’. Instances of ‘types’ called ‘entities’ represent the actual metadata objects that are managed. The Type System is a component that allows users to define and manage the types and entities. All metadata objects managed by Atlas out of the box (like Hive tables, for e.g.) are modelled using types and represented as entities. To store new types of metadata in Atlas, one needs to understand the concepts of the type system component.</p></div> +<div class="section"> +<h3><a name="Types"></a>Types</h3> +<p>A ‘Type’ in Atlas is a definition of how a particular type of metadata objects are stored and accessed. A type represents one or a collection of attributes that define the properties for the metadata object. Users with a development background will recognize the similarity of a type to a ‘Class’ definition of object oriented programming languages, or a ‘table schema’ of relational databases.</p> +<p>An example of a type that comes natively defined with Atlas is a Hive table. A Hive table is defined with these attributes:</p> +<div class="source"><pre class="prettyprint"> +Name: hive_table +TypeCategory: Entity +SuperTypes: DataSet +Attributes: + name: string + db: hive_db + owner: string + createTime: date + lastAccessTime: date + comment: string + retention: int + sd: hive_storagedesc + partitionKeys: array<hive_column> + aliases: array<string> + columns: array<hive_column> + parameters: map<string,string> + viewOriginalText: string + viewExpandedText: string + tableType: string + temporary: boolean +</pre></div> +<p>The following points can be noted from the above example:</p> +<p></p> +<ul> +<li>A type in Atlas is identified uniquely by a ‘name’</li> +<li>A type has a metatype. Atlas has the following metatypes: +<ul> +<li>Primitive metatypes: boolean, byte, short, int, long, float, double, biginteger, bigdecimal, string, date</li> +<li>Enum metatypes</li> +<li>Collection metatypes: array, map</li> +<li>Composite metatypes: Entity, Struct, Classification, Relationship</li></ul></li> +<li>Entity & Classification types can ‘extend’ from other types, called ‘supertype’ - by virtue of this, it will get to include the attributes that are defined in the supertype as well. This allows modellers to define common attributes across a set of related types etc. This is again similar to the concept of how Object Oriented languages define super classes for a class. It is also possible for a type in Atlas to extend from multiple super types. +<ul> +<li>In this example, every hive table extends from a pre-defined supertype called a ‘DataSet’. More details about this pre-defined types will be provided later.</li></ul></li> +<li>Types which have a metatype of ‘Entity’, ‘Struct’, ‘Classification’ or 'Relationship' can have a collection of attributes. Each attribute has a name (e.g. ‘name’) and some other associated properties. A property can be referred to using an expression type_name.attribute_name. It is also good to note that attributes themselves are defined using Atlas metatypes. +<ul> +<li>In this example, hive_table.name is a String, hive_table.aliases is an array of Strings, hive_table.db refers to an instance of a type called hive_db and so on.</li></ul></li> +<li>Type references in attributes, (like hive_table.db) are particularly interesting. Note that using such an attribute, we can define arbitrary relationships between two types defined in Atlas and thus build rich models. Note that one can also collect a list of references as an attribute type (e.g. hive_table.columns which represents a list of references from hive_table to hive_column type)</li></ul></div> +<div class="section"> +<h3><a name="Entities"></a>Entities</h3> +<p>An ‘entity’ in Atlas is a specific value or instance of an Entity ‘type’ and thus represents a specific metadata object in the real world. Referring back to our analogy of Object Oriented Programming languages, an ‘instance’ is an ‘Object’ of a certain ‘Class’.</p> +<p>An example of an entity will be a specific Hive Table. Say Hive has a table called ‘customers’ in the ‘default’ database. This table will be an ‘entity’ in Atlas of type hive_table. By virtue of being an instance of an entity type, it will have values for every attribute that are a part of the Hive table ‘type’, such as:</p> +<div class="source"><pre class="prettyprint"> +guid: "9ba387dd-fa76-429c-b791-ffc338d3c91f" +typeName: "hive_table" +status: "ACTIVE" +values: + name: “customers” + db: { "guid": "b42c6cfc-c1e7-42fd-a9e6-890e0adf33bc", "typeName": "hive_db" } + owner: “admin” + createTime: 1490761686029 + updateTime: 1516298102877 + comment: null + retention: 0 + sd: { "guid": "ff58025f-6854-4195-9f75-3a3058dd8dcf", "typeName": "hive_storagedesc" } + partitionKeys: null + aliases: null + columns: [ { "guid": ""65e2204f-6a23-4130-934a-9679af6a211f", "typeName": "hive_column" }, { "guid": ""d726de70-faca-46fb-9c99-cf04f6b579a6", "typeName": "hive_column" }, ...] + parameters: { "transient_lastDdlTime": "1466403208"} + viewOriginalText: null + viewExpandedText: null + tableType: “MANAGED_TABLE” + temporary: false +</pre></div> +<p>The following points can be noted from the example above:</p> +<p></p> +<ul> +<li>Every instance ofan entity type is identified by a unique identifier, a GUID. This GUID is generated by the Atlas server when the object is defined, and remains constant for the entire lifetime of the entity. At any point in time, this particular entity can be accessed using its GUID. +<ul> +<li>In this example, the ‘customers’ table in the default database is uniquely identified by the GUID "9ba387dd-fa76-429c-b791-ffc338d3c91f"</li></ul></li> +<li>An entity is of a given type, and the name of the type is provided with the entity definition. +<ul> +<li>In this example, the ‘customers’ table is a ‘hive_table.</li></ul></li> +<li>The values of this entity are a map of all the attribute names and their values for attributes that are defined in the hive_table type definition.</li> +<li>Attribute values will be according to the datatype of the attribute. Entity-type attributes will have value of type <a href="./AtlasObjectId.html">AtlasObjectId</a></li></ul> +<p>With this idea on entities, we can now see the difference between Entity and Struct metatypes. Entities and Structs both compose attributes of other types. However, instances of Entity types have an identity (with a GUID value) and can be referenced from other entities (like a hive_db entity is referenced from a hive_table entity). Instances of Struct types do not have an identity of their own. The value of a Struct type is a collection of attributes that are ‘embedded’ inside the entity itself.</p></div> +<div class="section"> +<h3><a name="Attributes"></a>Attributes</h3> +<p>We already saw that attributes are defined inside metatypes like Entity, Struct, Classification and Relationship. But we implistically referred to attributes as having a name and a metatype value. However, attributes in Atlas have some more properties that define more concepts related to the type system.</p> +<p>An attribute has the following properties:</p> +<div class="source"><pre class="prettyprint"> + name: string, + typeName: string, + isOptional: boolean, + isIndexable: boolean, + isUnique: boolean, + cardinality: enum +</pre></div> +<p>The properties above have the following meanings:</p> +<p></p> +<ul> +<li>name - the name of the attribute</li> +<li>dataTypeName - the metatype name of the attribute (native, collection or composite)</li> +<li>isComposite - +<ul> +<li>This flag indicates an aspect of modelling. If an attribute is defined as composite, it means that it cannot have a lifecycle independent of the entity it is contained in. A good example of this concept is the set of columns that make a part of a hive table. Since the columns do not have meaning outside of the hive table, they are defined as composite attributes.</li> +<li>A composite attribute must be created in Atlas along with the entity it is contained in. i.e. A hive column must be created along with the hive table.</li></ul></li> +<li>isIndexable - +<ul> +<li>This flag indicates whether this property should be indexed on, so that look ups can be performed using the attribute value as a predicate and can be performed efficiently.</li></ul></li> +<li>isUnique - +<ul> +<li>This flag is again related to indexing. If specified to be unique, it means that a special index is created for this attribute in <a href="./JanusGraph.html">JanusGraph</a> that allows for equality based look ups.</li> +<li>Any attribute with a true value for this flag is treated like a primary key to distinguish this entity from other entities. Hence care should be taken ensure that this attribute does model a unique property in real world. +<ul> +<li>For e.g. consider the name attribute of a hive_table. In isolation, a name is not a unique attribute for a hive_table, because tables with the same name can exist in multiple databases. Even a pair of (database name, table name) is not unique if Atlas is storing metadata of hive tables amongst multiple clusters. Only a cluster location, database name and table name can be deemed unique in the physical world.</li></ul></li></ul></li> +<li>multiplicity - indicates whether this attribute is required, optional, or could be multi-valued. If an entity’s definition of the attribute value does not match the multiplicity declaration in the type definition, this would be a constraint violation and the entity addition will fail. This field can therefore be used to define some constraints on the metadata information.</li></ul> +<p>Using the above, let us expand on the attribute definition of one of the attributes of the hive table below. Let us look at the attribute called ‘db’ which represents the database to which the hive table belongs:</p> +<div class="source"><pre class="prettyprint"> +db: + "name": "db", + "typeName": "hive_db", + "isOptional": false, + "isIndexable": true, + "isUnique": false, + "cardinality": "SINGLE" +</pre></div> +<p>Note the “isOptional=true” constraint - a table entity cannot be created without a db reference.</p> +<div class="source"><pre class="prettyprint"> +columns: + "name": "columns", + "typeName": "array<hive_column>", + "isOptional": optional, + "isIndexable": true, + “isUnique": false, + "constraints": [ { "type": "ownedRef" } ] +</pre></div> +<p>Note the “ownedRef” constraint for columns. By doing this, we are indicating that the defined column entities should always be bound to the table entity they are defined with.</p> +<p>From this description and examples, you will be able to realize that attribute definitions can be used to influence specific modelling behavior (constraints, indexing, etc) to be enforced by the Atlas system.</p></div> +<div class="section"> +<h3><a name="System_specific_types_and_their_significance"></a>System specific types and their significance</h3> +<p>Atlas comes with a few pre-defined system types. We saw one example (DataSet) in preceding sections. In this section we will see more of these types and understand their significance.</p> +<p><b>Referenceable</b>: This type represents all entities that can be searched for using a unique attribute called qualifiedName.</p> +<p><b>Asset</b>: This type extends Referenceable and adds attributes like name, description and owner. Name is a required attribute (isOptional=false), the others are optional.</p> +<p>The purpose of Referenceable and Asset is to provide modellers with way to enforce consistency when defining and querying entities of their own types. Having these fixed set of attributes allows applications and user interfaces to make convention based assumptions about what attributes they can expect of types by default.</p> +<p><b>Infrastructure</b>: This type extends Asset and typically can be used to be a common super type for infrastructural metadata objects like clusters, hosts etc.</p> +<p><b>DataSet</b>: This type extends Referenceable. Conceptually, it can be used to represent an type that stores data. In Atlas, hive tables, hbase_tables etc are all types that extend from DataSet. Types that extend DataSet can be expected to have a Schema in the sense that they would have an attribute that defines attributes of that dataset. For e.g. the columns attribute in a hive_table. Also entities of types that extend DataSet participate in data transformation and this transformation can be captured by Atlas via lineage (or provenance) graphs.</p> +<p><b>Process</b>: This type extends Asset. Conceptually, it can be used to represent any data transformation operation. For example, an ETL process that transforms a hive table with raw data to another hive table that stores some aggregate can be a specific type that extends the Process type. A Process type has two specific attributes, inputs and outputs. Both inputs and outputs are arrays of DataSet entities. Thus an instance of a Process type can use these inputs and outputs to capture how the lineage of a DataSet evolves.</p></div> + </div> + </div> + <hr/> + <footer> + <div class="container"> + <div class="row"> +Copyright é 2018 The Apache Software Foundation, Licensed under the Apache License, Version 2.0. + </div> + <p id="poweredBy" class="pull-right"><a href="http://maven.apache.org/"; title="Built by Maven" class="poweredBy"><img class="builtBy" alt="Built by Maven" src="./images/logos/maven-feather.png" /></a> +</p> + </div> + </footer> + </body> +</html>
