reuvenlax commented on a change in pull request #10767: Document Beam Schemas
URL: https://github.com/apache/beam/pull/10767#discussion_r400310180
##########
File path: website/src/documentation/programming-guide.md
##########
@@ -1970,7 +1976,1078 @@ records.apply("WriteToText",
See the [Beam-provided I/O Transforms]({{site.baseurl
}}/documentation/io/built-in/)
page for a list of the currently available I/O transforms.
-## 6. Data encoding and type safety {#data-encoding-and-type-safety}
+## 6. Schemas {#schemas}
+Often, the type of records being processed have an obvious structure. Common
Beam sources produce
+JSON, Avro, Protocol Buffer, or database row objects; all of these types have
well defined structures,
+structures that can often be determined by examining the type. Even within a
SDK pipeline, Simple Java POJOs
+(or equivalent structures in other languages) are often used as intermediate
types, and these also have a
+ clear structure that can be inferred by inspecting the class. By
understanding the structure of a pipeline’s
+ records, we can provide much more concise APIs for data processing.
+
+### 6.1. What is a schema {#what-is-a-schema}
+Most structured records share some common characteristics:
+* They can be subdivided into separate named fields. Fields usually have
string names, but sometimes - as in the case of indexed
+ tuples - have numerical indices instead.
+* There is a confined list of primitive types that a field can have. These
often match primitive types in most programming
+ languages: int, long, string, etc.
+* Often a field type can be marked as optional (sometimes referred to as
nullable) or required.
+
+In addition, often records have a nested structure. A nested structure occurs
when a field itself has subfields so the
+type of the field itself has a schema. Fields that are array or map types is
also a common feature of these structured
+records.
+
+For example, consider the following schema, representing actions in a
fictitious e-commerce company:
+
+**Purchase**
+<table>
+ <thead>
+ <tr class="header">
+ <th><b>Field Name</b></th>
+ <th><b>Field Type</b></th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>userId</td>
+ <td>STRING</td>
+ </tr>
+ <tr>
+ <td>itemId</td>
+ <td>INT64</td>
+ </tr>
+ <tr>
+ <td>shippingAddress</td>
+ <td>ROW(ShippingAddress)</td>
+ </tr>
+ <tr>
+ <td>cost</td>
+ <td>INT64</td>
+ </tr>
+ <tr>
+ <td>transactions</td>
+ <td>ARRAY[ROW(Transaction)]</td>
+ </tr>
+ </tbody>
+</table>
+<br/>
+
+**ShippingAddress**
+<table>
+ <thead>
+ <tr class="header">
+ <th><b>Field Name</b></th>
+ <th><b>Field Type</b></th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>streetAddress</td>
+ <td>STRING</td>
+ </tr>
+ <tr>
+ <td>city</td>
+ <td>STRING</td>
+ </tr>
+ <tr>
+ <td>state</td>
+ <td>nullable STRING</td>
+ </tr>
+ <tr>
+ <td>country</td>
+ <td>STRING</td>
+ </tr>
+ <tr>
+ <td>postCode</td>
+ <td>STRING</td>
+ </tr>
+ </tbody>
+</table>
+<br/>
+
+**Transaction**
+<table>
+ <thead>
+ <tr class="header">
+ <th><b>Field Name</b></th>
+ <th><b>Field Type</b></th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>bank</td>
+ <td>STRING</td>
+ </tr>
+ <tr>
+ <td>purchaseAmount</td>
+ <td>DOUBLE</td>
+ </tr>
+ </tbody>
+</table>
+<br/>
+
+Purchase event records are represented by the above purchase schema. Each
purchase event contains a shipping address, which
+is a nested row containing its own schema. Each purchase also contains a list
of credit-card transactions
+(a list, because a purchase might be split across multiple credit cards); each
item in the transaction list is a row
+with its own schema.
+
+This provides an abstract description of the types involved, one that is
abstracted away from any specific programming
+language.
+
+Schemas provide us a type-system for Beam records that is independent of any
specific programming-language type. There
+might be multiple Java classes that all have the same schema (for example a
Protocol-Buffer class or a POJO class),
+and Beam will allow us to seamlessly convert between these types. Schemas also
provide a simple way to reason about
+types across different programming-language APIs.
+
+A `PCollection` with a schema does not need to have a `Coder` specified, as
Beam knows how to encode and decode
+Schema rows.
+
+### 6.2. Schemas for programming language types {#schemas-for-pl-types}
+While schemas themselves are language independent, they are designed to embed
naturally into the programming languages
+of the Beam SDK being used. This allows Beam users to continue using native
types while reaping the advantage of
+having Beam understand their element schemas.
+
+ {:.language-java}
+ In Java you could use the following set of classes to represent the purchase
schema. Beam will automatically
+ infer the correct schema based on the members of the class.
+
+```java
+@DefaultSchema(JavaBeanSchema.class)
+public class Purchase {
+ public String getUserId(); // Returns the id of the user who made the
purchase.
+ public long getItemId(); // Returns the identifier of the item that was
purchased.
+ public ShippingAddress getShippingAddress(); // Returns the shipping
address, a nested type.
+ public long getCostCents(); // Returns the cost of the item.
+ public List<Transaction> getTransactions(); // Returns the transactions
that paid for this purchase (returns a list, since the purchase might be spread
out over multiple credit cards).
+
+ @SchemaCreate
+ public Purchase(String userId, long itemId, ShippingAddress shippingAddress,
long costCents,
+ List<Transaction> transactions) {
+ ...
+ }
+}
+
+@DefaultSchema(JavaBeanSchema.class)
+public class ShippingAddress {
+ public String getStreetAddress();
+ public String getCity();
+ @Nullable public String getState();
+ public String getCountry();
+ public String getPostCode();
+
+ @SchemaCreate
+ public ShippingAddress(String streetAddress, String city, @Nullable String
state, String country,
+ String postCode) {
+ ...
+ }
+}
+
+@DefaultSchema(JavaBeanSchema.class)
+public class Transaction {
+ public String getBank();
+ public double getPurchaseAmount();
+
+ @SchemaCreate
+ public Transaction(String bank, double purchaseAmount) {
+ ...
+ }
+}
+```
+
+Using JavaBean classes as above is one way to map a schema to Java classes.
However multiple Java classes might have
+the same schema, in which case the different Java types can often be used
interchangeably. For example, the above
+`Transaction` class has the same schema as the following class:
+
+```java
+@DefaultSchema(JavaFieldSchema.class)
+public class TransactionPojo {
+ public String bank;
+ public double purchaseAmount;
+}
+```
+
+So if we had two `PCollection`s as follows
+
+```java
+PCollection<Transaction> transactionBeans = readTransactionsAsJavaBean();
+PCollection<TransactionPojos> transactionPojos = readTransactionsAsPojo();
+```
+
+Then these two `PCollection`s would have the same schema, even though their
Java types would be different. This means
+for example the the following two code snippets are valid:
+
+```java
+transactionBeans.apply(ParDo.of(new DoFn<...>() {
+ @ProcessElement public void process(@Element TransactionPojo pojo) {
+ ...
+ }
+}));
+```
+
+and
+```java
+transactionPojos.apply(ParDo.of(new DoFn<...>() {
+ @ProcessElement public void process(@Element Transaction row) {
+ }
+}));
+```
+
+Even though the in both cases the `@Element` parameter differs from the the
`PCollection`'s Java type, since the
+schemas are the same Beam will automatically make the conversion. The built-in
`Convert` transform can also be used
+to translate between Java types of equivalent schemas, as detailed below.
+
+### 6.3. Schema definition {#schema-definition}
+The schema for a `PCollection` defines elements of that `PCollection` as an
ordered list of named fields. Each field
+has a name, a type, and possibly a set of user options. The type of a field
can be primitive or composite. The following
+are the primitive types currently supported by Beam:
Review comment:
I would prefer to wait until we actually can support that (i.e. until our
selection language supports escaping characters) before documenting that.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
