Apache Avro 資料來源指南

df = spark.read.format("avro").load("examples/src/main/resources/users.avro")
df.select("name", "favorite_color").write.format("avro").save("namesAndFavColors.avro")

val usersDF = spark.read.format("avro").load("examples/src/main/resources/users.avro")
usersDF.select("name", "favorite_color").write.format("avro").save("namesAndFavColors.avro")

Dataset<Row> usersDF = spark.read().format("avro").load("examples/src/main/resources/users.avro");
usersDF.select("name", "favorite_color").write().format("avro").save("namesAndFavColors.avro");

df <- read.df("examples/src/main/resources/users.avro", "avro")
write.df(select(df, "name", "favorite_color"), "namesAndFavColors.avro", "avro")

from pyspark.sql.avro.functions import from_avro, to_avro

# `from_avro` requires Avro schema in JSON string format.
jsonFormatSchema = open("examples/src/main/resources/user.avsc", "r").read()

df = spark\
  .readStream\
  .format("kafka")\
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")\
  .option("subscribe", "topic1")\
  .load()

# 1. Decode the Avro data into a struct;
# 2. Filter by column `favorite_color`;
# 3. Encode the column `name` in Avro format.
output = df\
  .select(from_avro("value", jsonFormatSchema).alias("user"))\
  .where('user.favorite_color == "red"')\
  .select(to_avro("user.name").alias("value"))

query = output\
  .writeStream\
  .format("kafka")\
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")\
  .option("topic", "topic2")\
  .start()

import org.apache.spark.sql.avro.functions._

// `from_avro` requires Avro schema in JSON string format.
val jsonFormatSchema = new String(Files.readAllBytes(Paths.get("./examples/src/main/resources/user.avsc")))

val df = spark
  .readStream
  .format("kafka")
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")
  .option("subscribe", "topic1")
  .load()

// 1. Decode the Avro data into a struct;
// 2. Filter by column `favorite_color`;
// 3. Encode the column `name` in Avro format.
val output = df
  .select(from_avro($"value", jsonFormatSchema) as $"user")
  .where("user.favorite_color == \"red\"")
  .select(to_avro($"user.name") as $"value")

val query = output
  .writeStream
  .format("kafka")
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")
  .option("topic", "topic2")
  .start()

import static org.apache.spark.sql.functions.col;
import static org.apache.spark.sql.avro.functions.*;

// `from_avro` requires Avro schema in JSON string format.
String jsonFormatSchema = new String(Files.readAllBytes(Paths.get("./examples/src/main/resources/user.avsc")));

Dataset<Row> df = spark
  .readStream()
  .format("kafka")
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")
  .option("subscribe", "topic1")
  .load();

// 1. Decode the Avro data into a struct;
// 2. Filter by column `favorite_color`;
// 3. Encode the column `name` in Avro format.
Dataset<Row> output = df
  .select(from_avro(col("value"), jsonFormatSchema).as("user"))
  .where("user.favorite_color == \"red\"")
  .select(to_avro(col("user.name")).as("value"));

StreamingQuery query = output
  .writeStream()
  .format("kafka")
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")
  .option("topic", "topic2")
  .start();

# `from_avro` requires Avro schema in JSON string format.
jsonFormatSchema <- paste0(readLines("examples/src/main/resources/user.avsc"), collapse=" ")

df <- read.stream(
  "kafka",
  kafka.bootstrap.servers = "host1:port1,host2:port2",
  subscribe = "topic1"
)

# 1. Decode the Avro data into a struct;
# 2. Filter by column `favorite_color`;
# 3. Encode the column `name` in Avro format.

output <- select(
  filter(
    select(df, alias(from_avro("value", jsonFormatSchema), "user")),
    column("user.favorite_color") == "red"
  ),
  alias(to_avro("user.name"), "value")
)

write.stream(
  output,
  "kafka",
  kafka.bootstrap.servers = "host1:port1,host2:port2",
  topic = "topic2"
)