[client-v2] Float NaN and Infinity are silently written into integer columns (NaN -> 0, Inf -> MAX_VALUE), also into Nullable(Int*)

Ouverte
#3,319 0 commentaires 0 réactions 0 personnes assignées Voir sur GitHub

Les mainteneurs répondent en général sous 1 jour

Personne n'a encore pris cette issue.

Évaluation

Difficulté
4/5
Temps estimé
3-5 jours
Accessibilité débutants
55/100
Type d'issue
Bug
Clarté
Clairement spécifiée
Activité
Active
Stack technique
java
Domaine
database

Piste de recherche

Start with client-v2/src/main/java/com/clickhouse/client/api/data_formats/internal/SerializerUtils.java, especially convertToInteger, convertToLong, and the NumberConverter.toBigInteger path. Trace how integer and Decimal targets handle non-finite Float and Double inputs, then locate or add coverage for the listed scalar and nested types. Done means those inputs fail with a clear client-side error instead of being written as zero or maximum values.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Description

Describe the bug

SerializerUtils.serializePrimitiveData converts a user-supplied Number to an integer column value with plain Java narrowing — convertToInteger / convertToLong call ((Number) value).intValue() / .longValue() (client-v2/src/main/java/com/clickhouse/client/api/data_formats/internal/SerializerUtils.java:1056-1082, used at lines 656-681 and 746).

Java narrowing of a non-finite double produces a legal-looking number instead of failing:

Written value Column Stored value
Double.NaN Nullable(Int32) 0 (not NULL, no error)
Double.POSITIVE_INFINITY Int32 2147483647
Double.POSITIVE_INFINITY Int64 9223372036854775807

No exception is raised and nothing is logged, so the row is silently corrupted. The server itself rejects both conversions (SELECT toInt32(nan) and SELECT toInt32(inf) fail with code 70, CANNOT_CONVERT_TYPE), so the client is more permissive than the server it writes to.

This is related to #3176 (silent wrapping of out-of-range integers) but is a distinct failure mode: the intValue() vs longValue() comparison suggested there (NumberConverter.toInt) does not catch NaN — both accessors return 0 for it — and does not catch +Inf for Int64 either. A non-finite check is needed on top of the range check.

ClickHouse server version

26.10.3.7 (local server at http://localhost:8123). The test below was run against it.

Reproduction

TestNG test in client-v2:

package com.clickhouse.client.insert;

import com.clickhouse.client.api.Client;
import com.clickhouse.client.api.data_formats.RowBinaryFormatWriter;
import com.clickhouse.client.api.insert.InsertResponse;
import com.clickhouse.client.api.insert.InsertSettings;
import com.clickhouse.client.api.metadata.TableSchema;
import com.clickhouse.client.api.query.GenericRecord;
import com.clickhouse.data.ClickHouseFormat;
import org.testng.annotations.Test;

import java.util.List;

public class NanIntScratchTest {

    @Test
    public void nanAndInfIntoIntegerColumns() throws Exception {
        try (Client client = new Client.Builder()
                .addEndpoint("http://localhost:8123")
                .setUsername("default").setPassword("")
                .compressServerResponse(false).compressClientRequest(false)
                .build()) {

            client.execute("DROP TABLE IF EXISTS nan_int_test").get();
            client.execute("CREATE TABLE nan_int_test (v Nullable(Int32), w Int32, i64 Int64, f Float64) ENGINE Memory").get();

            TableSchema schema = client.getTableSchema("nan_int_test");
            Object[][] rows = new Object[][]{
                    {13.0d, 13.0d, 13.0d, 13.0d},
                    {Double.NaN, Double.POSITIVE_INFINITY, Double.POSITIVE_INFINITY, 1.0d},
            };
            ClickHouseFormat format = ClickHouseFormat.RowBinary;
            try (InsertResponse r = client.insert("nan_int_test", out -> {
                RowBinaryFormatWriter w = new RowBinaryFormatWriter(out, schema, format);
                for (Object[] row : rows) {
                    for (int i = 0; i < row.length; i++) {
                        w.setValue(i + 1, row[i]);
                    }
                    w.commitRow();
                }
            }, format, new InsertSettings()).get()) {
                System.out.println("written rows = " + r.getWrittenRows());
            }

            for (GenericRecord rec : client.queryAll("SELECT v, w, i64, f FROM nan_int_test ORDER BY f")) {
                System.out.println("v=" + rec.getObject(1) + " w=" + rec.getInteger(2)
                        + " i64=" + rec.getLong(3) + " f=" + rec.getDouble(4));
            }
        }
    }
}

Actual output:

written rows = 2
v=0 w=2147483647 i64=9223372036854775807 f=1.0
v=13 w=13 i64=13 f=13.0

Expected: the insert fails with a clear client-side error for the non-finite values (as the server does), instead of writing 0 / MAX_VALUE.

Suggested fix

In client-v2/src/main/java/com/clickhouse/client/api/data_formats/internal/SerializerUtils.java, reject non-finite values before narrowing — in convertToInteger (line 1056) and convertToLong (line 1070), and in the NumberConverter.toBigInteger path used for UInt64/Int128/Int256, throw when a Float/Double argument is NaN or infinite. The same check is needed for Decimal targets. Nested containers (Array(Nullable(Int*)), Tuple, Map, LowCardinality(Nullable(Int*))) go through the same converters, so one check covers them.

Link

Relayed from the equivalent bug in clickhouse-connect: https://github.com/ClickHouse/clickhouse-connect/issues/1172

Langage dominant
Java
Étoiles
1.6k
Forks
649
Merge moyen
1 j 20 h
PR mergées (30 j)
39

Préparer son environnement

Par où commencer

  1. Lisez l'issue en entier, puis le guide de contribution du projet.
  2. Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
  3. Forkez le dépôt et travaillez sur une branche.
  4. Ouvrez une pull request qui référence le numéro de l'issue.

Autres issues de ClickHouse/clickhouse-java

Toutes les issues de ClickHouse/clickhouse-java

Issues similaires

Plus d'issues Java

Recevez les nouvelles issues par e-mail

Un résumé court des issues GitHub adaptées aux débutants.