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Working With AVRO and Parquet Files

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Working With AVRO and Parquet Files

Installing and working with tools for AVRO and Parquet files with Scala and Spark

· Big Data Zone
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With significant research and help from Srinivasarao Daruna, Data Engineer at airisdata.com

See the GitHub Repo for source code.

Step 0. Prerequisites:

For details on installation, see here: http://airisdata.com/scala-spark-resources-setup-learning/

Step 1: Clone this Repository into a directory (like c:/tools or /tools)

git clone https://github.com/airisdata/avroparquet.git

Step 1 - Alternate: You can download the Zip file from https://github.com/airisdata/avroparquet and unzip. It will name it avroparquet-master.

Step 2: Clone Parquet Map Reduce Tools (for Parquet Command Line Tools) Note: For this step you must have JDK 1.8 installed and in your path. Also you must have Maven 3.x installed and in your path.

git clone -b apache-parquet-1.8.0 https://github.com/apache/parquet-mr.git

cd parquet-mr cd parquet-tools mvn clean package -Plocal

Step 3: Copy the /target/parquet-tools-1.8.0.jar to a directory in your path

Step 4: Copy the meetup_parquet.parquet from the avroparquet.git repository to directory accessible from the parquet tools or the same directory.

Step 5: View the Binary Parquet File (meetup_parquet.parquet) using the parquet tools. This format works on Mac, you may need to set PATHs and change directory structure in Windows or Linux.

java -jar ./parquet-tools-1.8.0.jar cat meetup_parquet.parquet

Step 6: View the Schema for the Same Parquet File

java -jar ./parquet-tools-1.8.0.jar schema meetup_parquet.parquet

Step 7: Using AVRO Command Line Tools, download the AVRO tools.

You can either download with curl, wget, or directly from a browser using the link below:

wget http://apache.claz.org/avro/avro-1.8.0/java/avro-tools-1.8.0.jar

Step 8: Copy the avro-tools jar to your path or to your local directory.

Step 9: Copy an AVRO file to your local directory or an accessible directory from AVRO tools

    Download from here:  https://github.com/airisdata/avroparquet/blob/master/airisdata-meeetup/src/main/resources/avro_file.avro

wget https://github.com/airisdata/avroparquet/blob/master/airisdata-meeetup/src/main/resources/avro_file.avro

Step 10:

java -jar avro-tools-1.8.0.jar tojson --pretty avro_file.avro

For more information see:

Step 11: Avro and Parquet Java Instructions. Go to the directory where you downloaded https://github.com/airisdata/avroparquet/tree/master/airisdata-meeetup.
If you download the ZIP from GitHub it will be in directory avroparquet-master/airisdata-meetup

cd avroparquet-master cd airisdata-meetup

Step 12: Use Maven to build the package

mvn clean package

Step 13: AVRO File Processing

java -cp ./target/avro-work-1.0-SNAPSHOT-jar-with-dependencies.jar com.airisdata.utils.StorageFormatUtils avro write src/main/resources/avro_file.avro src/main/resources/old_schema.avsc

java -cp ./target/avro-work-1.0-SNAPSHOT-jar-with-dependencies.jar com.airisdata.utils.StorageFormatUtils avro read src/main/resources/avro_file.avro

java -cp ./target/avro-work-1.0-SNAPSHOT-jar-with-dependencies.jar com.airisdata.utils.StorageFormatUtils avro read src/main/resources/avro_file.avro src/main/resources/new_schema.avsc

cat src/main/resources/new_schema.avsc

Step 14: PARQUET File Processing

java -cp ./target/avro-work-1.0-SNAPSHOT-jar-with-dependencies.jar com.airisdata.utils.StorageFormatUtils parquet write src/main/resources/parquet_file.parquet src/main/resources/old_schema.avsc

java -cp ./target/avro-work-1.0-SNAPSHOT-jar-with-dependencies.jar com.airisdata.utils.StorageFormatUtils parquet read src/main/resources/parquet_file.parquet

Step 15: Kafka Setup. Download Kafka. (or for Mac you can do brew install kafka)

curl -O https://www.apache.org/dyn/closer.cgi?path=/kafka/

Step 16: Unzip/tar Kafka tar -xvf ./kafka_2.10-

Step 17: Run Zookeeper bin/zookeeper-server-start.sh config/zookeeper.properties

Step 18: Run Kafka bin/kafka-server-start.sh config/server.properties

Step 19: From your download directory: https://github.com/airisdata/avroparquet/tree/master/

Step 20: You must have Scala and SBT installed and in your path. You need Scala 2.10, JDK 8, and SBT 0.13 You can install these via brew.

Step 21: Build the Scala/Spark Program. You must have Spark 1.6.0+ installed

cd storageformats_meetup

sbt clean assembly

Step 22: Submit This jar to Spark to Run. You will need Spark installed and accessible in your path. (brew install spark or see previous meetups). Submit the Kafka Avro Producer. Spark-submit must be installed relevant to where you are.

spark-submit --class com.airisdata.streamingutils.ClickEmitter target/scala-2.10/storageformats_meetup-assembly-1.0.jar localhost:9092 test

Step 23: Submit Avro Consumer

spark-submit --class com.airisdata.streamingutils.KafkaAvroConsumer target/scala-2.10/storageformats_meetup-assembly-1.0.jar test 2

Step 24: View the Spark History server (if you are running that)


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big data ,spark ,parquet ,avro

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