Partitioning & Scale interview questions

1. A.the field whose value decides which node or shard a record is stored on
2. B.a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data
3. C.splitting one logical dataset across multiple machines so each holds only a subset of the rows
4. D.adding more commodity machines to share load, contrasted with buying a single bigger server

Answer + AI explanation with Pro

1. A.Horizontal scaling
2. B.Consistent hashing
3. C.Sharding
4. D.Partition key

Answer + AI explanation with Pro

1. A.Sharding — adding more commodity machines to share load, contrasted with buying a single bigger server
2. B.Sharding — a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data
3. C.Sharding — splitting one logical dataset across multiple machines so each holds only a subset of the rows
4. D.Sharding — the field whose value decides which node or shard a record is stored on

Answer + AI explanation with Pro

1. A.adding more commodity machines to share load, contrasted with buying a single bigger server
2. B.a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field
3. C.the field whose value decides which node or shard a record is stored on
4. D.a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data

Answer + AI explanation with Pro

1. A.Partition key
2. B.Sharding
3. C.Horizontal scaling
4. D.Consistent hashing

Answer + AI explanation with Pro

1. A.Partition key — the field whose value decides which node or shard a record is stored on
2. B.Partition key — a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field
3. C.Partition key — a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data
4. D.Partition key — splitting one logical dataset across multiple machines so each holds only a subset of the rows

Answer + AI explanation with Pro

1. A.splitting one logical dataset across multiple machines so each holds only a subset of the rows
2. B.adding more commodity machines to share load, contrasted with buying a single bigger server
3. C.the field whose value decides which node or shard a record is stored on
4. D.a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field

Answer + AI explanation with Pro

1. A.Horizontal scaling
2. B.Sharding
3. C.Hot partition
4. D.Consistent hashing

Answer + AI explanation with Pro

1. A.Horizontal scaling — the field whose value decides which node or shard a record is stored on
2. B.Horizontal scaling — a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field
3. C.Horizontal scaling — a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data
4. D.Horizontal scaling — adding more commodity machines to share load, contrasted with buying a single bigger server

Answer + AI explanation with Pro

1. A.a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field
2. B.a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data
3. C.the field whose value decides which node or shard a record is stored on
4. D.adding more commodity machines to share load, contrasted with buying a single bigger server

Answer + AI explanation with Pro

1. A.Partition key
2. B.Sharding
3. C.Horizontal scaling
4. D.Consistent hashing

Answer + AI explanation with Pro

1. A.Consistent hashing — a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field
2. B.Consistent hashing — a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data
3. C.Consistent hashing — the field whose value decides which node or shard a record is stored on
4. D.Consistent hashing — splitting one logical dataset across multiple machines so each holds only a subset of the rows

Answer + AI explanation with Pro

1. A.a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field
2. B.the field whose value decides which node or shard a record is stored on
3. C.splitting one logical dataset across multiple machines so each holds only a subset of the rows
4. D.adding more commodity machines to share load, contrasted with buying a single bigger server

Answer + AI explanation with Pro

1. A.Partition key
2. B.Hot partition
3. C.Sharding
4. D.Horizontal scaling

Answer + AI explanation with Pro

1. A.Hot partition — the field whose value decides which node or shard a record is stored on
2. B.Hot partition — a single shard that receives a disproportionate share of traffic because of a poorly chosen distribution field
3. C.Hot partition — splitting one logical dataset across multiple machines so each holds only a subset of the rows
4. D.Hot partition — a placement scheme that maps keys and nodes onto a ring so adding or removing a node moves only a small fraction of data

Answer + AI explanation with Pro