İkincil İndekslerle Sorgulama: GSI'lar ve LSI'lar

DynamoDB queries efficiently only by the primary key (partition key, optionally plus sort key). To query by other attributes you need a secondary index.

• Scanning the whole table is slow and costly
• Indexes give you efficient alternate access paths

A secondary index is an alternate view of your table data, organized by a different key. DynamoDB keeps it in sync automatically as you write to the base table.

A GSI can use any attributes as its partition and sort key, different from the table key. It has its own throughput and can be created anytime.

• Query by a completely different attribute
• Spans all partitions of the table
• Eventually consistent reads only

An LSI shares the table partition key but uses a different sort key. It must be created at table creation time and supports strongly consistent reads.

Choosing between them:

• GSI: different partition key, created anytime, eventually consistent
• LSI: same partition key, created with the table, strongly consistent

You specify the index name and its key schema. Reads and writes against the index are billed separately from the base table.

To query a GSI you pass its name and the index key condition. The query returns items matching that alternate key.

An index projection controls which attributes are copied into it: keys only, a selected set, or all. Projecting fewer attributes saves storage but may force a base-table fetch.

• KEYS_ONLY: smallest, just keys
• INCLUDE: keys plus chosen attributes
• ALL: full copy, biggest

GSIs consume their own read and write capacity. Every base-table write that affects an indexed attribute also writes to the GSI, so over-indexing increases cost.

If an item lacks the index key attribute, it is not written to the index. This creates a sparse index, an efficient way to query only items that have a certain attribute set.

In DynamoDB you design indexes around your access patterns, not the other way around. List the queries your app needs, then create the minimal set of indexes that serve them.

You learned how secondary indexes enable querying DynamoDB by non-primary-key attributes. You compared GSIs (flexible keys, created anytime, eventually consistent) with LSIs (shared partition key, created with the table, strongly consistent), and covered projections, throughput, sparse indexes, and access-pattern-first design.