Showing posts with the label Zookeeper

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How to Check Column Nulls and Replace: Pandas

Here is a post that shows how to count Nulls and replace them with the value you want in the Pandas Dataframe. We have explained the process in two steps - Counting and Replacing the Null values. Count null values (column-wise) in Pandas ## count null values column-wise null_counts = df.isnull(). sum() print(null_counts) ``` Output: ``` Column1    1 Column2    1 Column3    5 dtype: int64 ``` In the above code, we first create a sample Pandas DataFrame `df` with some null values. Then, we use the `isnull()` function to create a DataFrame of the same shape as `df`, where each element is a boolean value indicating whether that element is null or not. Finally, we use the `sum()` function to count the number of null values in each column of the resulting DataFrame. The output shows the count of null values column-wise. to count null values column-wise: ``` df.isnull().sum() ``` ##Code snippet to count null values row-wise: ``` df.isnull().sum(axis=1) ``` In the above code, `df` is the Panda

MemSQL in Advanced Data Analytics

Why use a battery of "complicated" and "immature" tools like Kafka, Zookeeper, and NoSQL databases to support low-latency big data applications when you can use a durable, consistent, SQL-compliant in-memory database? This is the question NewSQL in-memory database vendors MemSQL and VoltDB are posing to big-data developers who are trying to build real-time applications. MemSQL this week announced a two-way, high-performance MemSQL Spark Connector designed to complement the fast-growing Apache Spark in-memory analytics platform.   "There's a lot of excitement about Spark, but many data scientists struggle with complexity and the high degree of expertise to work with related data pipelines," said Erik Frenkiel, CEO and cofounder of MemSQL, in a phone interview with InformationWeek. "As a database, MemSQL offers durability and transaction support, so it can simplify those real-time data pipelines, providing the ability to ingest data and qu