{"id":110549,"date":"2021-06-25T07:00:00","date_gmt":"2021-06-25T04:00:00","guid":{"rendered":"https:\/\/www.javacodegeeks.com\/?p=110549"},"modified":"2021-06-18T19:56:16","modified_gmt":"2021-06-18T16:56:16","slug":"bigquery-storage-api-arrow","status":"publish","type":"post","link":"https:\/\/www.javacodegeeks.com\/2021\/06\/bigquery-storage-api-arrow.html","title":{"rendered":"BigQuery Storage API: Arrow"},"content":{"rendered":"

Previously we had an introduction<\/a> on the BigQuery Storage API. As explained the storage API of BigQuery supports two formats. For this tutorial we will choose the Arrow Format.<\/p>\n

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\"\"<\/a><\/figure>\n<\/div>\n

First let\u2019s import the dependencies. The BigQuery storage API binary does not come with a library to parse Arrow. This way the consumer receives the binaries in an Arrow format, and it\u2019s up to the consumer on how to consume the binaries and what libraries to use.<\/p>\n

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<<\/code>dependencyManagement<\/code>><\/code><\/div>\n
        <\/code><<\/code>dependencies<\/code>><\/code><\/div>\n
            <\/code><<\/code>dependency<\/code>><\/code><\/div>\n
                <\/code><<\/code>groupId<\/code>>com.google.cloud<\/<\/code>groupId<\/code>><\/code><\/div>\n
                <\/code><<\/code>artifactId<\/code>>libraries-bom<\/<\/code>artifactId<\/code>><\/code><\/div>\n
                <\/code><<\/code>version<\/code>>20.5.0<\/<\/code>version<\/code>><\/code><\/div>\n
                <\/code><<\/code>type<\/code>>pom<\/<\/code>type<\/code>><\/code><\/div>\n
                <\/code><<\/code>scope<\/code>>import<\/<\/code>scope<\/code>><\/code><\/div>\n
            <\/code><\/<\/code>dependency<\/code>><\/code><\/div>\n
        <\/code><\/<\/code>dependencies<\/code>><\/code><\/div>\n
    <\/code><\/<\/code>dependencyManagement<\/code>><\/code><\/div>\n
 <\/div>\n
    <\/code><<\/code>dependencies<\/code>><\/code><\/div>\n
        <\/code><<\/code>dependency<\/code>><\/code><\/div>\n
            <\/code><<\/code>groupId<\/code>>com.google.cloud<\/<\/code>groupId<\/code>><\/code><\/div>\n
            <\/code><<\/code>artifactId<\/code>>google-cloud-bigquerystorage<\/<\/code>artifactId<\/code>><\/code><\/div>\n
        <\/code><\/<\/code>dependency<\/code>><\/code><\/div>\n
        <\/code><<\/code>dependency<\/code>><\/code><\/div>\n
            <\/code><<\/code>groupId<\/code>>org.apache.arrow<\/<\/code>groupId<\/code>><\/code><\/div>\n
            <\/code><<\/code>artifactId<\/code>>arrow-vector<\/<\/code>artifactId<\/code>><\/code><\/div>\n
            <\/code><<\/code>version<\/code>>4.0.0<\/<\/code>version<\/code>><\/code><\/div>\n
        <\/code><\/<\/code>dependency<\/code>><\/code><\/div>\n
        <\/code><<\/code>dependency<\/code>><\/code><\/div>\n
            <\/code><<\/code>groupId<\/code>>org.apache.arrow<\/<\/code>groupId<\/code>><\/code><\/div>\n
            <\/code><<\/code>artifactId<\/code>>arrow-memory-netty<\/<\/code>artifactId<\/code>><\/code><\/div>\n
            <\/code><<\/code>version<\/code>>4.0.0<\/<\/code>version<\/code>><\/code><\/div>\n
        <\/code><\/<\/code>dependency<\/code>><\/code><\/div>\n
    <\/code><\/<\/code>dependencies<\/code>><\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n

As mentioned before<\/a>, when we use Arrow we need to import a library for the memory allocation Arrow needs.<\/p>\n

We shall create first a plain Arrow Reader. This Reader will be BigQuery agnostic. This is one of the benefits when we use a platform-language independent format.<\/p>\n

An Arrow Binary shall be submitted to the reader with the schema and the rows shall be printed in CSV format.<\/p>\n

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package<\/code> com.gkatzioura.bigquery.storage.api.arrow;<\/code><\/div>\n
 <\/div>\n
import<\/code> java.io.IOException;<\/code><\/div>\n
import<\/code> java.util.ArrayList;<\/code><\/div>\n
import<\/code> java.util.List;<\/code><\/div>\n
 <\/div>\n
import<\/code> org.apache.arrow.memory.BufferAllocator;<\/code><\/div>\n
import<\/code> org.apache.arrow.memory.RootAllocator;<\/code><\/div>\n
import<\/code> org.apache.arrow.util.Preconditions;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.FieldVector;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.VectorLoader;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.VectorSchemaRoot;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.ipc.ReadChannel;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.ipc.message.MessageSerializer;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.types.pojo.Field;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.types.pojo.Schema;<\/code><\/div>\n
import<\/code> org.apache.arrow.vector.util.ByteArrayReadableSeekableByteChannel;<\/code><\/div>\n
 <\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.ArrowRecordBatch;<\/code><\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.ArrowSchema;<\/code><\/div>\n
 <\/div>\n
public<\/code> class<\/code> ArrowReader <\/code>implements<\/code> AutoCloseable {<\/code><\/div>\n
 <\/div>\n
    <\/code>private<\/code> final<\/code> BufferAllocator allocator = <\/code>new<\/code> RootAllocator(Long.MAX_VALUE);<\/code><\/div>\n
 <\/div>\n
    <\/code>private<\/code> final<\/code> VectorSchemaRoot root;<\/code><\/div>\n
    <\/code>private<\/code> final<\/code> VectorLoader loader;<\/code><\/div>\n
 <\/div>\n
    <\/code>public<\/code> ArrowReader(ArrowSchema arrowSchema) <\/code>throws<\/code> IOException {<\/code><\/div>\n
        <\/code>Schema schema =<\/code><\/div>\n
                <\/code>MessageSerializer.deserializeSchema(<\/code><\/div>\n
                        <\/code>new<\/code> ReadChannel(<\/code><\/div>\n
                                <\/code>new<\/code> ByteArrayReadableSeekableByteChannel(<\/code><\/div>\n
                                        <\/code>arrowSchema.getSerializedSchema().toByteArray())));<\/code><\/div>\n
 <\/div>\n
        <\/code>Preconditions.checkNotNull(schema);<\/code><\/div>\n
        <\/code>List<FieldVector> vectors = <\/code>new<\/code> ArrayList<>();<\/code><\/div>\n
        <\/code>for<\/code> (Field field : schema.getFields()) {<\/code><\/div>\n
            <\/code>vectors.add(field.createVector(allocator));<\/code><\/div>\n
        <\/code>}<\/code><\/div>\n
 <\/div>\n
        <\/code>root = <\/code>new<\/code> VectorSchemaRoot(vectors);<\/code><\/div>\n
        <\/code>loader = <\/code>new<\/code> VectorLoader(root);<\/code><\/div>\n
    <\/code>}<\/code><\/div>\n
 <\/div>\n
    <\/code>public<\/code> void<\/code> processRows(ArrowRecordBatch batch) <\/code>throws<\/code> IOException {<\/code><\/div>\n
        <\/code>org.apache.arrow.vector.ipc.message.ArrowRecordBatch deserializedBatch =<\/code><\/div>\n
                <\/code>MessageSerializer.deserializeRecordBatch(<\/code><\/div>\n
                        <\/code>new<\/code> ReadChannel(<\/code><\/div>\n
                                <\/code>new<\/code> ByteArrayReadableSeekableByteChannel(<\/code><\/div>\n
                                        <\/code>batch.getSerializedRecordBatch().toByteArray())),<\/code><\/div>\n
                        <\/code>allocator);<\/code><\/div>\n
 <\/div>\n
        <\/code>loader.load(deserializedBatch);<\/code><\/div>\n
        <\/code>deserializedBatch.close();<\/code><\/div>\n
        <\/code>System.out.println(root.contentToTSVString());<\/code><\/div>\n
        <\/code>root.clear();<\/code><\/div>\n
    <\/code>}<\/code><\/div>\n
 <\/div>\n
    <\/code>@Override<\/code><\/div>\n
    <\/code>public<\/code> void<\/code> close() <\/code>throws<\/code> Exception {<\/code><\/div>\n
        <\/code>root.close();<\/code><\/div>\n
        <\/code>allocator.close();<\/code><\/div>\n
    <\/code>}<\/code><\/div>\n
 <\/div>\n
}<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n

The constructor will have the schema injected, then the schema root shall be created.
Pay attention that we receive the schema in a binary form, it\u2019s up to us and our library on how to read it.

<\/div> <\/div><\/p>\n
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Schema schema =<\/code><\/div>\n
                <\/code>MessageSerializer.deserializeSchema(<\/code><\/div>\n
                        <\/code>new<\/code> ReadChannel(<\/code><\/div>\n
                                <\/code>new<\/code> ByteArrayReadableSeekableByteChannel(<\/code><\/div>\n
                                        <\/code>arrowSchema.getSerializedSchema().toByteArray())));<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n

You can find more on reading Arrow data on this<\/a> tutorial.<\/p>\n

Then on to our main class which is the one with any BigQuery logic needed.<\/p>\n

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package<\/code> com.gkatzioura.bigquery.storage.api.arrow;<\/code><\/div>\n
 <\/div>\n
import<\/code> org.apache.arrow.util.Preconditions;<\/code><\/div>\n
 <\/div>\n
import<\/code> com.google.api.gax.rpc.ServerStream;<\/code><\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.BigQueryReadClient;<\/code><\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.CreateReadSessionRequest;<\/code><\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.DataFormat;<\/code><\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.ReadRowsRequest;<\/code><\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.ReadRowsResponse;<\/code><\/div>\n
import<\/code> com.google.cloud.bigquery.storage.v1.ReadSession;<\/code><\/div>\n
 <\/div>\n
public<\/code> class<\/code> ArrowMain {<\/code><\/div>\n
 <\/div>\n
    <\/code>public<\/code> static<\/code> void<\/code> main(String[] args) <\/code>throws<\/code> Exception {<\/code><\/div>\n
 <\/div>\n
        <\/code>String projectId = System.getenv(<\/code>\"PROJECT_ID\"<\/code>);<\/code><\/div>\n
 <\/div>\n
        <\/code>try<\/code> (BigQueryReadClient client = BigQueryReadClient.create()) {<\/code><\/div>\n
            <\/code>String parent = String.format(<\/code>\"projects\/%s\"<\/code>, projectId);<\/code><\/div>\n
 <\/div>\n
            <\/code>String srcTable =<\/code><\/div>\n
                    <\/code>String.format(<\/code><\/div>\n
                            <\/code>\"projects\/%s\/datasets\/%s\/tables\/%s\"<\/code>,<\/code><\/div>\n
                            <\/code>projectId, System.getenv(<\/code>\"DATASET\"<\/code>), System.getenv(<\/code>\"TABLE\"<\/code>));<\/code><\/div>\n
 <\/div>\n
            <\/code>ReadSession.Builder sessionBuilder =<\/code><\/div>\n
                    <\/code>ReadSession.newBuilder()<\/code><\/div>\n
                               <\/code>.setTable(srcTable)<\/code><\/div>\n
                               <\/code>.setDataFormat(DataFormat.ARROW);<\/code><\/div>\n
 <\/div>\n
            <\/code>CreateReadSessionRequest.Builder builder =<\/code><\/div>\n
                    <\/code>CreateReadSessionRequest.newBuilder()<\/code><\/div>\n
                                            <\/code>.setParent(parent)<\/code><\/div>\n
                                            <\/code>.setReadSession(sessionBuilder)<\/code><\/div>\n
                                            <\/code>.setMaxStreamCount(<\/code>1<\/code>);<\/code><\/div>\n
            <\/code>ReadSession session = client.createReadSession(builder.build());<\/code><\/div>\n
 <\/div>\n
            <\/code>try<\/code> (ArrowReader reader = <\/code>new<\/code> ArrowReader(session.getArrowSchema())) {<\/code><\/div>\n
                <\/code>Preconditions.checkState(session.getStreamsCount() > <\/code>0<\/code>);<\/code><\/div>\n
 <\/div>\n
                <\/code>String streamName = session.getStreams(<\/code>0<\/code>).getName();<\/code><\/div>\n
 <\/div>\n
                <\/code>ReadRowsRequest readRowsRequest =<\/code><\/div>\n
                        <\/code>ReadRowsRequest.newBuilder().setReadStream(streamName).build();<\/code><\/div>\n
 <\/div>\n
                <\/code>ServerStream<ReadRowsResponse> stream = client.readRowsCallable().call(readRowsRequest);<\/code><\/div>\n
                <\/code>for<\/code> (ReadRowsResponse response : stream) {<\/code><\/div>\n
                    <\/code>Preconditions.checkState(response.hasArrowRecordBatch());<\/code><\/div>\n
                    <\/code>reader.processRows(response.getArrowRecordBatch());<\/code><\/div>\n
                <\/code>}<\/code><\/div>\n
            <\/code>}<\/code><\/div>\n
        <\/code>}<\/code><\/div>\n
    <\/code>}<\/code><\/div>\n
 <\/div>\n
}<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n

A BigQuery client is created. Then we create a session request with a max number of streams. We do have to specify that the format to be used will be Arrow.
Once we get a Response, the response will contain the initiated the Session, the Arrow schema and the streams that we shall use to retrieve the Data.
For each stream there has to be a ReadRowsRequest in order to fetch the data.
Our next example will focus on reading data in Avro format<\/a>.<\/p>\n

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\n

Published on Java Code Geeks with permission by Emmanouil Gkatziouras, partner at our JCG program<\/a>. See the original article here: BigQuery Storage API: Arrow<\/a><\/p>\n

Opinions expressed by Java Code Geeks contributors are their own.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Previously we had an introduction on the BigQuery Storage API. As explained the storage API of BigQuery supports two formats. For this tutorial we will choose the Arrow Format. First let\u2019s import the dependencies. The BigQuery storage API binary does not come with a library to parse Arrow. This way the consumer receives the binaries …<\/p>\n","protected":false},"author":936,"featured_media":112,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[372],"class_list":["post-110549","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-enterprise-java","tag-big-data"],"yoast_head":"\nBigQuery Storage API: Arrow - Java Code Geeks<\/title>\n<meta name=\"description\" content=\"Interested to learn about BigQuery Storage? 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