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PostgreSQL DBA
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Channel Posts
| 2 |  No text... | 268 |
| 3 |  No text... | 259 |
| 4 |  Configuration Parameters | 247 |
| 5 | CREATE TABLE orders (
order_id SERIAL PRIMARY KEY,
customer_id INTEGER,
order_date DATE,
order_total NUMERIC
) PARTITION BY RANGE (order_date);
CREATE TABLE orders_y2023 PARTITION OF orders
FOR VALUES FROM ('2023-01-01') TO ('2024-01-01');
CREATE TABLE orders_y2024 PARTITION OF orders
FOR VALUES FROM ('2024-01-01') TO ('2025-01-01');
-- Add an index to each partition
CREATE INDEX idx_orders_y2023_customer_id ON orders_y2023 (customer_id);
CREATE INDEX idx_orders_y2024_customer_id ON orders_y2024 (customer_id); | 197 |
| 6 |  No text... | 154 |
| 7 |  No text... | 160 |
| 8 |  No text... | 140 |
| 9 |  Beyond indexing, several query optimization techniques can significantly improve performance. | 123 |
| 10 | Unused Indexes: Identify and remove unused indexes to reduce write overhead. The pg_stat_all_indexes view provides information about index usage. | 126 |
| 11 | Index Bloat: As data is inserted, updated, and deleted, indexes can become fragmented and bloated, leading to performance degradation. Rebuild indexes periodically using the REINDEX command. | 122 |
| 12 | Statistics: PostgreSQL relies on statistics to estimate the cost of different query plans. Inaccurate statistics can lead to suboptimal plan choices. Regularly update statistics using the ANALYZE command. | 127 |
| 13 | Partial indexes index only a subset of the table's rows, based on a condition. This can reduce index size and improve performance when queries frequently filter on that condition. | 132 |
| 14 | Composite indexes index multiple columns. The order of columns in a composite index is important. The most frequently used column in WHERE clauses should come first. | 130 |
| 15 |  No text... | 127 |
| 16 | Indexes are crucial for improving query performance, but they also add overhead to write operations. Choosing the right indexes and maintaining them properly is essential. | 131 |
| 17 | Filtering: Where clauses that filter the data. If a filter is being applied after a large amount of data has already been processed, this is a sign the query could be optimized. | 127 |
| 18 | Rows: The estimated number of rows returned by each operation. Significant discrepancies between estimated and actual rows (observed with EXPLAIN ANALYZE) can indicate inaccurate statistics, leading the planner to choose a suboptimal plan. | 119 |
| 19 | Cost: The estimated cost of each operation. The planner uses a cost model to estimate the resources required to perform each operation. Higher costs usually indicate potential bottlenecks. | 115 |
| 20 |  No text... | 116 |
