|
| 1 | +--- |
| 2 | +title: Java Typed API |
| 3 | +sidebar_position: 3 |
| 4 | +--- |
| 5 | + |
| 6 | +# Java Typed API |
| 7 | + |
| 8 | +Fluss provides a Typed API that allows you to work directly with Java POJOs (Plain Old Java Objects) instead of `InternalRow` objects. This simplifies development by automatically mapping your Java classes to Fluss table schemas. |
| 9 | + |
| 10 | +:::info |
| 11 | +The Typed API provides a more user-friendly experience but comes with a performance cost due to the overhead of converting between POJOs and internal row formats. For high-performance use cases, consider using the lower-level `InternalRow` API. |
| 12 | +::: |
| 13 | + |
| 14 | +## Defining POJOs |
| 15 | + |
| 16 | +To use the Typed API, define a Java class where the field names and types match your Fluss table schema. |
| 17 | + |
| 18 | +```java |
| 19 | +public class User { |
| 20 | + public Integer id; |
| 21 | + public String name; |
| 22 | + public Integer age; |
| 23 | + |
| 24 | + public User() {} |
| 25 | + |
| 26 | + public User(Integer id, String name, Integer age) { |
| 27 | + this.id = id; |
| 28 | + this.name = name; |
| 29 | + this.age = age; |
| 30 | + } |
| 31 | + |
| 32 | + // Getters, setters, equals, hashCode, toString... |
| 33 | +} |
| 34 | +``` |
| 35 | + |
| 36 | +The supported type mappings are: |
| 37 | + |
| 38 | +| Fluss Type | Java Type | |
| 39 | +|---|---| |
| 40 | +| INT | Integer | |
| 41 | +| BIGINT | Long | |
| 42 | +| STRING | String | |
| 43 | +| BOOLEAN | Boolean | |
| 44 | +| FLOAT | Float | |
| 45 | +| DOUBLE | Double | |
| 46 | +| DECIMAL | BigDecimal | |
| 47 | +| DATE | LocalDate | |
| 48 | +| TIME | LocalTime | |
| 49 | +| TIMESTAMP | LocalDateTime | |
| 50 | +| TIMESTAMP_LTZ | Instant | |
| 51 | +| BINARY / BYTES | byte[] | |
| 52 | + |
| 53 | +## Writing Data |
| 54 | + |
| 55 | +### Append Writer |
| 56 | + |
| 57 | +For append-only tables (Log tables), use `TypedAppendWriter`. |
| 58 | + |
| 59 | +```java |
| 60 | +TablePath path = TablePath.of("my_db", "users_log"); |
| 61 | +try (Table table = conn.getTable(path)) { |
| 62 | + TypedAppendWriter<User> writer = table.newAppend().createTypedWriter(User.class); |
| 63 | + |
| 64 | + writer.append(new User(1, "Alice", 30)); |
| 65 | + writer.append(new User(2, "Bob", 25)); |
| 66 | + |
| 67 | + writer.flush(); |
| 68 | +} |
| 69 | +``` |
| 70 | + |
| 71 | +### Upsert Writer |
| 72 | + |
| 73 | +For primary key tables, use `TypedUpsertWriter`. |
| 74 | + |
| 75 | +```java |
| 76 | +TablePath path = TablePath.of("my_db", "users_pk"); |
| 77 | +try (Table table = conn.getTable(path)) { |
| 78 | + TypedUpsertWriter<User> writer = table.newUpsert().createTypedWriter(User.class); |
| 79 | + |
| 80 | + // Insert or Update |
| 81 | + writer.upsert(new User(1, "Alice", 31)); |
| 82 | + |
| 83 | + // Delete |
| 84 | + writer.delete(new User(1, null, null)); // Only PK fields are needed for delete |
| 85 | + |
| 86 | + writer.flush(); |
| 87 | +} |
| 88 | +``` |
| 89 | + |
| 90 | +### Partial Updates |
| 91 | + |
| 92 | +You can perform partial updates by specifying the columns to update. |
| 93 | + |
| 94 | +```java |
| 95 | +// Update only 'name' and 'age' for the user with id 1 |
| 96 | +Upsert upsert = table.newUpsert().partialUpdate("name", "age"); |
| 97 | +TypedUpsertWriter<User> writer = upsert.createTypedWriter(User.class); |
| 98 | + |
| 99 | +User partialUser = new User(); |
| 100 | +partialUser.id = 1; |
| 101 | +partialUser.name = "Alice Updated"; |
| 102 | +partialUser.age = 32; |
| 103 | + |
| 104 | +writer.upsert(partialUser); |
| 105 | +writer.flush(); |
| 106 | +``` |
| 107 | + |
| 108 | +## Reading Data |
| 109 | + |
| 110 | +Use `TypedLogScanner` to read data as POJOs. |
| 111 | + |
| 112 | +```java |
| 113 | +Scan scan = table.newScan(); |
| 114 | +TypedLogScanner<User> scanner = scan.createTypedLogScanner(User.class); |
| 115 | + |
| 116 | +try (CloseableIterator<TypedScanRecord<User>> iterator = scanner.subscribeFromBeginning()) { |
| 117 | + while (iterator.hasNext()) { |
| 118 | + TypedScanRecord<User> record = iterator.next(); |
| 119 | + ChangeType changeType = record.getChangeType(); |
| 120 | + User user = record.getValue(); |
| 121 | + |
| 122 | + System.out.println(changeType + ": " + user); |
| 123 | + } |
| 124 | +} |
| 125 | +``` |
| 126 | + |
| 127 | +### Projections |
| 128 | + |
| 129 | +You can also use projections with the Typed API. The POJO fields that are not part of the projection will be null. |
| 130 | + |
| 131 | +```java |
| 132 | +// Only read 'id' and 'name' |
| 133 | +TypedLogScanner<User> scanner = table.newScan() |
| 134 | + .project("id", "name") |
| 135 | + .createTypedLogScanner(User.class); |
| 136 | +``` |
| 137 | + |
| 138 | +## Lookups |
| 139 | + |
| 140 | +For primary key tables, you can perform lookups using a POJO that represents the primary key. |
| 141 | + |
| 142 | +```java |
| 143 | +// Define a POJO for the key |
| 144 | +public class UserId { |
| 145 | + public Integer id; |
| 146 | + |
| 147 | + public UserId(Integer id) { this.id = id; } |
| 148 | +} |
| 149 | + |
| 150 | +// Create a TypedLookuper |
| 151 | +TypedLookuper<UserId> lookuper = table.newLookup().createTypedLookuper(UserId.class); |
| 152 | + |
| 153 | +// Perform lookup |
| 154 | +CompletableFuture<LookupResult> resultFuture = lookuper.lookup(new UserId(1)); |
| 155 | +LookupResult result = resultFuture.get(); |
| 156 | + |
| 157 | +if (result != null) { |
| 158 | + // Convert the result row back to a User POJO if needed |
| 159 | + // Note: You might need a RowToPojoConverter for this part if you want the full User object |
| 160 | + // or you can access fields from the InternalRow directly. |
| 161 | +} |
| 162 | +``` |
| 163 | + |
| 164 | +## Performance Considerations |
| 165 | + |
| 166 | +While the Typed API offers convenience and type safety, it involves an additional layer of conversion between your POJOs and Fluss's internal binary row format (`InternalRow`). This conversion process (serialization and deserialization) introduces CPU overhead. |
| 167 | + |
| 168 | +Benchmarks indicate that using the Typed API can be roughly **2x slower** than using the `InternalRow` API directly for both writing and reading operations. |
| 169 | + |
| 170 | +**Recommendation:** |
| 171 | +* Use the **Typed API** for ease of use, rapid development, and when type safety is preferred over raw performance. |
| 172 | +* Use the **InternalRow API** for high-throughput, latency-sensitive applications where performance is critical. |
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