# logical Published articles for logical. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Waiting for PostgreSQL 19 - Add support for EXCEPT TABLE in ALTER PUBLICATION. DevFeed: [Waiting for PostgreSQL 19 - Add support for EXCEPT TABLE in ALTER PUBLICATION.]() Original publisher: [Read original article]() Author: depesz Published: 2026-03-26T11:46:24Z Content type: article Language: en Sources: [select \* from depesz;]() Topics: [PostgreSQL](), [syntax]() Tags: [alter](), [commit](), [except](), [logical](), [pg19](), [postgresql](), [publication](), [replication](), [table](), [uncategorized](), [waiting]() ### AI overview This article discusses a PostgreSQL 19 patch adding EXCEPT TABLE support to ALTER PUBLICATION. The change allows modifying a publication's table exclusion list, though the example notes that specifying an exclusion for one publication replaced its previous exclusion list. ### Source excerpt On 20th of March 2026, Amit Kapila committed patch: Add support for EXCEPT TABLE in ALTER PUBLICATION. Following commit fd366065e0, which added EXCEPT TABLE support to CREATE PUBLICATION, this commit extends ALTER PUBLICATION to allow modifying the exclusion list. New Syntax: ALTER PUBLICATION name SET publication_all_object [, ... ] where publication_all_object is ... Continue reading "Waiting for PostgreSQL 19 - Add support for EXCEPT TABLE in ALTER PUBLICATION." ## Waiting for PostgreSQL 19 - Allow table exclusions in publications via EXCEPT TABLE. DevFeed: [Waiting for PostgreSQL 19 - Allow table exclusions in publications via EXCEPT TABLE.]() Original publisher: [Read original article]() Author: depesz Published: 2026-03-18T11:15:16Z Content type: article Language: en Sources: [select \* from depesz;]() Topics: [PostgreSQL](), [Replication](), [Databases]() Tags: [except](), [logical](), [new-feature](), [pg19](), [postgresql](), [publication](), [replication](), [uncategorized](), [waiting]() ### AI overview A PostgreSQL patch adds EXCEPT TABLE support to CREATE PUBLICATION ... FOR ALL TABLES, allowing selected tables to be excluded from logical replication. The article explains the existing publication options and notes that altering an existing FOR ALL TABLES publication to add exclusions is not currently supported. ### Source excerpt On 4th of March 2026, Amit Kapila committed patch: Allow table exclusions in publications via EXCEPT TABLE. Extend CREATE PUBLICATION ... FOR ALL TABLES to support the EXCEPT TABLE syntax. This allows one or more tables to be excluded. The publisher will not send the data of excluded tables to the subscriber. To ... Continue reading "Waiting for PostgreSQL 19 - Allow table exclusions in publications via EXCEPT TABLE." ## Waiting for PostgreSQL 19 - Sequence synchronization in logical replication. DevFeed: [Waiting for PostgreSQL 19 - Sequence synchronization in logical replication.]() Original publisher: [Read original article]() Author: depesz Published: 2025-11-11T12:24:23Z Content type: tutorial Language: en Sources: [select \* from depesz;]() Topics: [PostgreSQL](), [Replication](), [Sequences]() Tags: [benchmark](), [logical](), [pg19](), [postgresql](), [psql](), [publications](), [replication](), [sequence](), [sequences](), [synchronization](), [uncategorized](), [upgrade](), [upgrades](), [waiting]() ### AI overview This article demonstrates PostgreSQL 19's planned sequence synchronization for logical replication. It sets up source and destination databases, tests sequence synchronization, finds that resynchronization must be manually invoked, and reports that synchronizing 10,000 sequences took about one second in the author's test. ### Source excerpt First, on 9th of October 2025, Amit Kapila committed patch: Add "ALL SEQUENCES" support to publications. This patch adds support for the ALL SEQUENCES clause in publications, enabling synchronization/replication of all sequences that is useful for upgrades. Publications can now include all sequences via FOR ALL SEQUENCES. psql enhancements: \d shows publications for ... Continue reading "Waiting for PostgreSQL 19 - Sequence synchronization in logical replication." ## Postgres backups: Logical vs. Physical an overview DevFeed: [Postgres backups: Logical vs. Physical an overview]() Original publisher: [Read original article]() Author: Map Published: 2017-09-03T20:55:56Z Content type: tutorial Language: en Sources: [Craig Kerstiens]() Topics: [backups](), [Database](), [Databases](), [data]() Tags: [backing-up](), [backup](), [backups](), [checksums](), [dump](), [environments](), [logical](), [overview](), [pg-dump](), [portable](), [postgres](), [postgresql](), [production](), [sql](), [wal]() ### AI overview This article explains PostgreSQL's two backup types: logical backups, which are portable and can target selected tables but add database load, and physical backups, which consist of the database's bytes on disk. It also discusses checksums, corruption detection, and the role of the write-ahead log. ### Source excerpt It's not a very disputed topic that you should backup your database, and further test your backups. What is a little less discussed, at least for Postgres, is the types of backups that exist. Within Postgres there are two forms of backups and understanding them is a useful foundation for anyone working with Postgres. The two backup types are Physical: which consist of the actual bytes on disk, Logical: which is a more portable format. Let's dig into each a bit more so you can better assess which makes sense for you. Logical backups Logical backups are the most well known type within Postgres. This is what you get when you run pg_dump against a database. There are a number of different formats you can get from logical backups and Postgres does a good job of making it easy to compress and configure this backup how you see fit. When a logical backup is run against a database it is not throttled, this introduces a noticable load on your database. As it's reading the data from disk and generating (in layman terms) a bunch of SQL INSERT statements, it has to actually see the data. It's of note that older Postgres databases (read: prior to 9.3) there were no checksums against your database. Checksums are just one tool for you to help check against data corruption. Because a logical dump has to actually read and generate the data to insert it will discover any corruption that exists for you. This portable format is also very useful to pull down copies from production to different environments. I.e. if you need a copy of production data down on your local laptop pg_dump is the way to do it. Logical backups are also database specific, but then allow you to dump only certain tables. All in all logical backups bring some good features, but come at two cost: Load on your system The backup contains data as of the time when it ran Physical backups Physical backups are another option when it comes to backing up your database. As we mentioned earlier it is the physical bytes on disk ## Zero-One Laws for Random Graphs DevFeed: [Zero-One Laws for Random Graphs]() Original publisher: [Read original article]() Published: 2015-02-09T09:00:00Z Content type: article Language: en Sources: [Jeremy Kun]() Topics: [Graphs](), [Math and Logic]() Tags: [big-o-notation](), [connectivity](), [countability](), [distribution](), [erdos-renyi](), [graphs](), [logic](), [logical](), [mathematics](), [model-theory](), [network-science](), [parameter](), [random-graph](), [random-graphs](), [statement](), [vertex]() ### AI overview This article introduces zero-one laws for Erdős-Rényi random graphs. It explains that many graph properties, including properties expressible in first-order logic, have probabilities that tend toward zero or one as the graph grows, with behavior determined by relevant thresholds or constant edge probabilities. ### Source excerpt Last time we saw a number of properties of graphs, such as connectivity, where the probability that an Erdős-Rényi random graph $ G(n,p)$ satisfies the property is asymptotically either zero or one. And this zero or one depends on whether the parameter $ p$ is above or below a universal threshold (that depends only on $ n$ and the property in question). To remind the reader, the Erdős-Rényi random "graph" $ G(n,p)$ is a distribution over graphs that you draw from by including each edge independently with probability $ p$. ## A problem that is not (properly) PAC-learnable DevFeed: [A problem that is not (properly) PAC-learnable]() Original publisher: [Read original article]() Published: 2014-04-21T10:00:16Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Learning](), [math](), [Math and Logic]() Tags: [algorithm](), [boolean](), [boolean-satisfiability](), [classes](), [computational-complexity](), [computational-learning-theory](), [learning-theory](), [logical](), [math](), [mathematics](), [misconceptions](), [np](), [np-completeness](), [pac-learning](), [reduction](), [rp]() ### AI overview This technical learning-theory article presents a standard example of a problem that is not learnable under the previously introduced PAC model, then explains how a more expressive hypothesis class changes that result. Its addendum clarifies that 3-term DNF formulas are not shown to be unlearnable under the standard PAC definition, only under the earlier restricted definition. ### Source excerpt In a previous post we introduced a learning model called Probably Approximately Correct (PAC). We saw an example of a concept class that was easy to learn: intervals on the real line (and more generally, if you did the exercise, axis-aligned rectangles in a fixed dimension). One of the primary goals of studying models of learning is to figure out what is learnable and what is not learnable in the various models. ## PostgreSQL 9.4 - Looking up (with JSONB and logical decoding) DevFeed: [PostgreSQL 9.4 - Looking up (with JSONB and logical decoding)]() Original publisher: [Read original article]() Author: Map Published: 2014-03-24T20:55:56Z Content type: article Language: en Sources: [Craig Kerstiens]() Topics: [PostgreSQL](), [JSON](), [Decoding](), [Database](), [Replication]() Tags: [decoding](), [indexing](), [jsonb](), [logical](), [postgres](), [postgresql]() ### AI overview This article examines PostgreSQL 9.4 features, focusing on JSONB and logical decoding. It explains how JSONB provides binary JSON document storage and how GIN indexes can automatically index document keys and values. The supplied text begins discussing logical decoding but is incomplete. ### Source excerpt Just a few weeks back I wrote a article discussing many of the things that were likely to miss making the 9.4 PostgreSQL release. Since that post a few weeks ago the landscape has already changed, and much more for the positive. The lesson here, is never count Postgres out. As Bruce discussed in a recent interview, Postgres is slow and steady, but much like the turtle can win the race. So onto the actual features: JSONB JSON has existed for a while in Postgres. Though the JSON that exists today simply validates that your text is valid JSON, then goes on to store it in a text field. This is fine, but not overly performant. If you do need some flexibility of your schema and performance without much effort then hstore may already work for you today, you can of course read more on this in an old post comparing hstore to json. But let's assume you do want JSON and a full document store, which is perfectly reasonable. Your option today is still best with the JSON datatype. And if you're retrieving full documents this is fine, however if you're searching/filtering on values within those documents then you need to take advantage of some functional indexing. You can do this some of the built-in operators or with full JS in Postgres. This is a little more work, but also very possible to get good performance. Finally, onto the perfect world, where JSON isn't just text in your database. For some time there's been a discussion around hstore and its future progress and of course the future of JSON in Postgres. These two worlds have finally heavily converged for PostgreSQL 9.4 giving you the best of both worlds. With what was known as hstore2, by The Russians under the covers, and collective efforts on JSONB (Binary representation of JSON) which included all the JSON interfaces you'd expect. We now have full document storage and awesome performance with little effort. Digging in a little further, why does it matter that its a binary representation? Well under the covers building o