The hottest Querying Substack posts right now

Choosing the right genre and comparative titles for your book is really important when querying agents. Make sure your comps support the genre you want to pitch.
Upmarket fiction is a blend of literary and commercial styles, focusing on good writing while still being accessible to a wide audience. It's crucial to know where your book fits in this spectrum.
Don't stress too much about pitching your book perfectly. The right agent will understand the essence of your work, even if your initial genre label isn't spot on.

There are nine agents currently looking for memoirs, which is a great opportunity for writers in that genre.
Upcoming changes to the newsletter will include more insights and tips about the querying process from experienced writers and agents.
Writers can use the Query Hotline and new chat features to ask questions and share experiences about getting published.

When querying agents about a new book, it's fine to directly email them if they previously showed interest. Just make sure to update the subject line and include your new manuscript.
Publishing is a partnership, so approach agents with respect and mutual understanding. Both sides need to feel heard and valued for a successful collaboration.
If you get a book deal, don't stress about tight deadlines for sequels. It's more likely that your publisher will not pursue a sequel if your first book doesn't sell well.

Comp titles in pitching are about giving an idea of the flavor of your book, not the recipe.
Non-fiction comp titles should be carefully chosen to avoid market saturation or irrelevance.
Avoid using overly complicated or grandiose comp titles, keep them simple for more success.

You can easily build KQL query templates for Azure services by using the Open Query option in the Azure portal.
The Open Query option in Azure Resource Graph Explorer auto-builds a KQL query for the specific service you're accessing.
Not all Azure services have the Open Query option, only those that utilize Azure Graph for information.

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In a B-Tree based storage system like BoltDB, you need to be explicit about indexing and querying data, unlike relational databases that automatically handle indexing.
By maintaining bidirectional mappings between terms and targets, and incorporating priorities for sorting, you can efficiently retrieve and sort data without unnecessary overhead.
BoltDB enables indexing data by any criteria, offering flexibility in ranking objects and improving relevance in search results, while eliminating the overhead associated with SQL databases.

Consider how to use a semantic layer with streaming data to enhance efficiency and data processing.
Streaming data warehouses handle storage differently than batch data warehouses, keeping fresh data in-memory and reducing compute cost.
The semantic layer abstracts entities, attributes, and metrics, aiding in managing and optimizing queries on streaming data.

Stateful stream processors and streaming databases have different approaches in handling data ingestion and state persistence.
Stream processors require knowing and embedding state manipulation logic in advance, while streaming databases offer ad-hoc manipulation by consumers.
Stream processors are ideal for automated, machine-driven decision-making, while streaming databases cater to human decision-makers needing fast, ad-hoc data access.

You can easily build KQL query templates for Azure services by utilizing the Open Query option in the Azure portal.
The Open Query option takes you to Azure Resource Graph Explorer and generates a KQL query specific to the service you're accessing.
Not all Azure services have this option, so be sure to check the All Services pane in Azure to see which services support KQL queries.

A semantic data model includes pre-built calculations and relationships.
There are two main types of queries: lookup and aggregating.
In a semantic data model, querying involves selecting dimensions and measures, simplifying the process.