# BigQuery untuk Data Engineering (Data Engineering)

> Arsitektur serverless, partitioning, clustering, biaya, UDFs, federated queries, scheduled queries, materialized views

- 20 pertanyaan wawancara
- Mid-Level
- [Pertanyaan Wawancara: Data Engineering](https://sharpskill.dev/id/technologies/data-engineering/pertanyaan-wawancara.md)

## 1. Arsitektur penyimpanan apa yang digunakan BigQuery?

**Jawaban**

BigQuery menggunakan arsitektur serverless dengan penyimpanan kolom (columnar storage) yang disebut Capacitor. Arsitektur ini memisahkan storage dan compute, memungkinkan scaling independen dan tagihan terpisah. Columnar storage dioptimalkan untuk query analitik karena hanya membaca kolom yang diperlukan, secara signifikan mengurangi I/O.

## 2. Apa keuntungan utama dari partitioning tabel di BigQuery?

**Jawaban**

Partitioning membagi tabel besar menjadi segmen yang lebih kecil berdasarkan kolom (biasanya tanggal). Selama query, BigQuery dapat melewati partisi yang tidak relevan (partition pruning), mengurangi jumlah data yang dipindai. Ini meningkatkan kinerja dan mengurangi biaya karena BigQuery menagih berdasarkan volume data yang diproses.

## 3. Tipe partitioning apa yang tersedia di BigQuery?

**Jawaban**

BigQuery mendukung tiga tipe partitioning: berdasarkan kolom DATE atau TIMESTAMP (paling umum), berdasarkan rentang integer (INTEGER RANGE), dan berdasarkan waktu ingesti (_PARTITIONTIME). Partitioning berdasarkan tanggal direkomendasikan untuk data time-series karena memungkinkan partition pruning yang efisien pada filter tanggal.

## 17 pertanyaan lagi tersedia

- Apa perbedaan antara partitioning dan clustering di BigQuery?
- Bagaimana cara mengoptimalkan biaya query di BigQuery?

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